Geographic object processing method, device, electronic device and computer storage medium

Abstract

The present application discloses a geographic object processing method, apparatus, electronic device, and computer storage medium. The method comprises: obtaining a non-ontology library geographic object and an ontology library geographic object set, wherein the non-ontology library geographic object is a geographic object that does not originate from the ontology library geographic object set; determining the address text matching degree and geographic location matching degree between the non-ontology library geographic object and any ontology library geographic object in the ontology library object set; determining whether the non-ontology library geographic object and any ontology library geographic object are the same geographic object based on the address text matching degree and the geographic location matching degree; and if so, associating the non-ontology library geographic object with the ontology library geographic object of the same geographic object in a mapping relationship table. This method improves the mounting rate and mounting accuracy of non-ontology library geographic objects and ontology library geographic objects.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a geographic object processing method, device, electronic device and computer storage medium. Background Art

[0002] With the rapid development and increasing maturity of China's real estate industry, it has become a new growth point for the national economy. Home valuation is a prerequisite and foundation for real estate management and economic accounting. Home valuation, also known as real estate valuation, refers to the estimation of a home's value based on factors such as its structure, standard, location, materials used, area, and condition.

[0003] In the field of real estate valuation, real estate valuation models are commonly used to estimate a property's value. Using digital methods to estimate real estate value can improve the accuracy of online real estate valuations. When using real estate valuation models to estimate a property's value, the characteristic information of the neighborhoods in the ontology database is input into the model to obtain a valuation result. Since the characteristic information of neighborhoods in the ontology database often comes from multiple other neighborhoods (not neighborhoods in the ontology database), accurate mapping of neighborhoods in the ontology database and neighborhoods in the housing stock are crucial to the real estate valuation model. Mapping involves matching neighborhoods in the ontology database to neighborhoods in the ontology database, thereby expanding the information in the ontology database. The main purpose of mapping is to associate neighborhoods in the ontology database with information on various neighborhoods in the housing stock, thereby enriching the features in the ontology database and improving the accuracy of the real estate valuation model. Since the addresses of neighborhoods in the ontology database are primarily based on information in geographic information systems, while the addresses of the housing stock neighborhoods come from a variety of sources, this makes mapping more difficult. Furthermore, current listing mapping is primarily based on the similarity between the address strings of the housing stock neighborhood and the ontology database neighborhood, resulting in relatively low mapping accuracy and listing rates.

[0004] Therefore, how to provide a method to improve the accuracy of listings and the rate of listings is an urgent problem that needs to be solved. Summary of the Invention

[0005] The embodiment of the present application provides a geographic object processing method, which improves the mounting rate and mounting accuracy of non-ontology library geographic objects and ontology library geographic objects.

[0006] An embodiment of the present application provides a geographic object processing method, comprising: obtaining a non-ontology library geographic object and an ontology library geographic object set, wherein the non-ontology library geographic object is a geographic object that does not originate from the ontology library geographic object set; determining an address text matching degree and a geographic location matching degree between the non-ontology library geographic object and any one of the ontology library geographic objects in the ontology library geographic object set; judging whether the non-ontology library geographic object and any one of the ontology library geographic objects are the same geographic object based on the address text matching degree and the geographic location matching degree; and if so, associating the non-ontology library geographic object with the ontology library geographic object of the same geographic object in a mapping relationship table.

[0007] Optionally, determining the address text matching degree and geographic location matching degree between the non-ontology library geographic object and any ontology library geographic object in the ontology library geographic object set includes:

[0008] Determining an address text matching degree between the non-ontology library geographic object and any one ontology library geographic object in the ontology library geographic object set based on the address text data of the non-ontology library geographic object and the address text data of any one ontology library geographic object in the ontology library geographic object set;

[0009] The geographical location matching degree between the non-ontology library geographical object and the any ontology library geographical object is determined according to the geographical location data of the non-ontology library geographical object and the geographical location data of the any ontology library geographical object.

[0010] Optionally, determining the address text matching degree between the non-ontology library geographic object and any one ontology library geographic object in the ontology library geographic object set based on the address text data of the non-ontology library geographic object and the address text data of any one ontology library geographic object includes:

[0011] Determine whether the geographical object name data of the non-ontology library geographical object is the same as the geographical object name data of any ontology library geographical object in the ontology library geographical object set, and obtain a first determination result;

[0012] According to the first judgment result, the address text matching degree between the non-ontology library geographical object and the any one ontology library geographical object is determined.

[0013] Optionally, determining the geographic location matching degree between the non-ontology library geographic object and the any ontology library geographic object based on the geographic location data of the non-ontology library geographic object and the geographic location data of the any ontology library geographic object includes:

[0014] Determining geographical distance data between the non-ontology library geographical object and the any one ontology library geographical object based on the geographical location data of the non-ontology library geographical object and the geographical location data of the any one ontology library geographical object;

[0015] Determine whether the geographic distance data is less than a first geographic distance data threshold, and obtain a second determination result;

[0016] According to the second judgment result, a geographical location matching degree between the non-ontology library geographical object and any one of the ontology library geographical objects is determined.

[0017] Optionally, judging whether the non-ontology library geographical object and any one of the ontology library geographical objects are the same geographical object according to the address text matching degree and the geographical location matching degree includes:

[0018] If the address text matching degree is higher than the address text matching degree threshold, and the geographic location matching degree is higher than the geographic location matching degree threshold, it is determined that the non-ontology library geographic object and the any ontology library geographic object are the same geographic object.

[0019] Optionally, determining the address text matching degree between the non-ontology library geographic object and any one ontology library geographic object in the ontology library geographic object set based on the address text data of the non-ontology library geographic object and the address text data of any one ontology library geographic object includes:

[0020] Determining a matching degree of the point of interest data between the non-ontology library geographical object and any one ontology library geographical object in the ontology library geographical object set based on the point of interest data of the non-ontology library geographical object and the point of interest data of any one ontology library geographical object in the ontology library geographical object set;

[0021] Determining a name suffix matching degree between the non-ontology library geographical object and any one ontology library geographical object in the ontology library geographical object set based on the geographical object name suffix data of the non-ontology library geographical object and the geographical object name suffix data of any one ontology library geographical object in the ontology library geographical object set;

[0022] The address text matching degree between the non-ontology library geographic object and the any one ontology library geographic object is determined according to the point of interest data matching degree and the name suffix matching degree.

[0023] Optionally, determining the address text matching degree between the non-ontology library geographic object and any one of the ontology library geographic objects based on the POI data matching degree and the name suffix matching degree includes:

[0024] Deleting unnecessary name information in the point of interest data of the non-ontology library geographic object to obtain key point of interest data of the non-ontology library geographic object;

[0025] Deleting unnecessary name information in the point of interest data of any one of the ontology library geographic objects, and obtaining key point of interest data of any one of the ontology library geographic objects;

[0026] Determine whether the key point of interest data of the non-ontology library geographic object is the same as the key point of interest data of any one of the ontology library geographic objects to obtain a third determination result;

[0027] According to the third judgment result, a matching degree of point of interest data between the non-ontology library geographic object and any one of the ontology library geographic objects is determined.

[0028] Optionally, determining the name suffix matching degree between the non-ontology library geographical object and any one ontology library geographical object in the ontology library geographical object set based on the geographical object name suffix data of the non-ontology library geographical object and the geographical object name suffix data of any one ontology library geographical object in the ontology library geographical object set includes:

[0029] Determine the character string length value of the geographic object name data of the non-ontology library geographic object;

[0030] Determine the character string length value of the geographic object name data of any geographic object in the ontology library;

[0031] If the character string length value of the geographic object name data of any ontology library geographic object is less than the character string length value of the geographic object name data of the non-ontology library geographic object, then truncating a character string corresponding to a first character string length difference from the last character of the geographic object name data of the non-ontology library geographic object forward as a first truncated character string, wherein the first character string length difference is the difference between the character string length value of the geographic object name data of the non-ontology library geographic object and the character string length value of the geographic object name data of any ontology library geographic object;

[0032] determining whether the name data corresponding to the first intercepted character string is identical to the geographic object name data of any geographic object in the ontology library, to obtain a fourth determination result;

[0033] According to the fourth judgment result, a name suffix matching degree between the non-ontology library geographical object and the any one ontology library geographical object is determined.

[0034] Optionally, determining the name suffix matching degree between the non-ontology library geographical object and any one ontology library geographical object in the ontology library geographical object set based on the geographical object name suffix data of the non-ontology library geographical object and the geographical object name suffix data of any one ontology library geographical object in the ontology library geographical object set includes:

[0035] Determine the character string length value of the geographic object name data of the non-ontology library geographic object;

[0036] Determine the character string length value of the geographic object name data of any geographic object in the ontology library;

[0037] If the character string length value of the geographic object name data of the non-ontology library geographic object is less than the character string length value of the geographic object name data of any one of the ontology library geographic objects, then truncating a character string corresponding to a second character string length difference from the last character of the geographic object name data of any one of the ontology library geographic objects as a second truncated character string, wherein the second character string length difference is the difference between the character string length value of the geographic object name data of any one of the ontology library geographic objects and the character string length value of the geographic object name data of the non-ontology library geographic object;

[0038] determining whether the name data corresponding to the second intercepted character string is identical to the geographic object name data of the non-ontology library geographic object, to obtain a fifth determination result;

[0039] According to the fifth judgment result, a name suffix matching degree between the non-ontology library geographical object and any one of the ontology library geographical objects is determined.

[0040] Optionally, also include:

[0041] Determine whether the non-ontology library geographical object and any one of the ontology library geographical objects are parent-child geographical objects, to obtain a sixth determination result;

[0042] The determining, based on the address text matching degree and the geographic location matching degree, whether the non-ontology library geographic object and any one of the ontology library geographic objects are the same geographic object includes: determining, based on the address text matching degree, the geographic location matching degree, and the sixth determination result, whether the non-ontology library geographic object and any one of the ontology library geographic objects are the same geographic object.

[0043] Optionally, the determining whether the non-ontology library geographical object and any one of the ontology library geographical objects are parent-child geographical objects to obtain a sixth determination result includes:

[0044] Determine a sub-geographical object of any ontology library geographic object as the ontology library sub-geographical object;

[0045] Determine the geographic object name data of the ontology library sub-geographic object;

[0046] Determine a geographic object name matching degree between the geographic object name data of the ontology library sub-geographic object and the geographic object name data of the non-ontology library geographic object;

[0047] According to the geographic object name matching degree between the geographic object name data of the ontology library child geographic object and the geographic object name data of the non-ontology library geographic object, it is determined whether the non-ontology library geographic object and any one of the ontology library geographic objects are parent-child geographic objects to obtain the sixth judgment result.

[0048] Optionally, judging whether the non-ontology library geographical object and any one of the ontology library geographical objects are the same geographical object according to the address text matching degree, the geographical location matching degree, and the sixth judgment result includes:

[0049] If the address text matching degree is higher than the address text matching degree threshold, the geographic location matching degree is higher than the geographic location matching degree threshold, and the non-ontology library geographic object and any one of the ontology library geographic objects are not parent-child geographic objects, then it is determined that the non-ontology library geographic object and any one of the ontology library geographic objects are the same geographic object.

[0050] Optionally, determining the geographic location matching degree between the non-ontology library geographic object and the any ontology library geographic object based on the geographic location data of the non-ontology library geographic object and the geographic location data of the any ontology library geographic object includes:

[0051] Determining geographical distance data between the non-ontology library geographical object and the any one ontology library geographical object based on the geographical location data of the non-ontology library geographical object and the geographical location data of the any one ontology library geographical object;

[0052] Determine whether the geographic distance data is less than a second geographic distance data threshold to obtain a seventh determination result;

[0053] According to the seventh judgment result, a geographical location matching degree between the non-ontology library geographical object and any one of the ontology library geographical objects is determined.

[0054] Optionally, determining the address text matching degree between the non-ontology library geographic object and any one ontology library geographic object in the ontology library geographic object set based on the address text data of the non-ontology library geographic object and the address text data of any one ontology library geographic object includes:

[0055] Determine the character string length value of the geographic object name data of the non-ontology library geographic object;

[0056] Determine the character string length value of the geographic object name data of any geographic object in the ontology library;

[0057] According to the character string length value of the geographical object name data of the non-ontology library geographical object and the character string length value of the geographical object name data of any one of the ontology library geographical objects, determining the larger character string length value between the character string length value of the geographical object name data of the non-ontology library geographical object and the character string length value of the geographical object name data of any one of the ontology library geographical objects as the target character string length value;

[0058] Traverse all characters in the character string of the geographical object name data of the non-ontology library geographical object and the geographical object name data of any one of the ontology library geographical objects;

[0059] Determine a first substring between the first character in the character string corresponding to the geographic object name data of the non-ontology library geographic object and the character preceding the currently traversed character, and a second substring between the first character in the character string corresponding to the geographic object name data of any ontology library geographic object and the currently traversed character;

[0060] Determine, based on the first substring and the second substring, a first longest common subsequence length value between the geographic object name data of the non-ontology library geographic object and the geographic object name data of any one of the ontology library geographic objects;

[0061] Determine a third substring between the first character in the character string corresponding to the geographic object name data of the non-ontology library geographic object and the currently traversed character, and a fourth substring between the first character in the character string corresponding to the geographic object name data of any ontology library geographic object and the character immediately preceding the currently traversed character;

[0062] Determine, based on the third substring and the fourth substring, a second longest common subsequence length value between the geographic object name data of the non-ontology library geographic object and the geographic object name data of any one of the ontology library geographic objects;

[0063] Determine a longest common subsequence length value between the first longest common subsequence length value and the second longest common subsequence length value as a target longest common subsequence length value;

[0064] Determine whether a ratio of the target longest common subsequence length to the target character string length is greater than a preset ratio threshold, to obtain an eighth determination result;

[0065] According to the eighth judgment result, a name matching degree between the non-ontology library geographical object and any ontology library geographical object in the ontology library geographical object set is determined.

[0066] Optionally, also include:

[0067] Determine whether the non-ontology library geographical object and any one of the ontology library geographical objects are parent-child geographical objects, to obtain a ninth determination result;

[0068] The determining, based on the address text matching degree and the geographic location matching degree, whether the non-ontology library geographic object and any one of the ontology library geographic objects are the same geographic object includes: determining, based on the address text matching degree, the geographic location matching degree and the ninth judgment result, whether the non-ontology library geographic object and any one of the ontology library geographic objects are the same geographic object.

[0069] Optionally, the determining whether the non-ontology library geographical object and any one of the ontology library geographical objects are parent-child geographical objects to obtain a ninth determination result includes:

[0070] Determine a sub-geographical object of any ontology library geographic object as the ontology library sub-geographical object;

[0071] Determine the geographic object name data of the ontology library sub-geographic object;

[0072] Determine a geographic object name matching degree between the geographic object name data of the ontology library sub-geographic object and the geographic object name data of the non-ontology library geographic object;

[0073] According to the geographic object name matching degree between the geographic object name data of the ontology library child geographic object and the geographic object name data of the non-ontology library geographic object, it is determined whether the non-ontology library geographic object and any one of the ontology library geographic objects are parent-child geographic objects to obtain the ninth judgment result.

[0074] Optionally, judging whether the non-ontology library geographical object and any one of the ontology library geographical objects are the same geographical object based on the address text matching degree, the geographical location matching degree, and the ninth judgment result includes:

[0075] If the address text matching degree is higher than the address text matching degree threshold, the geographic location matching degree is higher than the geographic location matching degree threshold, and the non-ontology library geographic object and any one of the ontology library geographic objects are not parent-child geographic objects, then it is determined that the non-ontology library geographic object and any one of the ontology library geographic objects are the same geographic object.

[0076] Optionally, determining the geographic location matching degree between the non-ontology library geographic object and the any ontology library geographic object based on the geographic location data of the non-ontology library geographic object and the geographic location data of the any ontology library geographic object includes:

[0077] Determining geographical distance data between the non-ontology library geographical object and the any one ontology library geographical object based on the geographical location data of the non-ontology library geographical object and the geographical location data of the any one ontology library geographical object;

[0078] determining whether the geographic distance data is less than a third geographic distance data threshold, to obtain a tenth determination result;

[0079] According to the tenth judgment result, a geographical location matching degree between the non-ontology library geographical object and any one of the ontology library geographical objects is determined.

[0080] Optionally, determining the address text matching degree between the non-ontology library geographic object and any one ontology library geographic object in the ontology library geographic object set based on the address text data of the non-ontology library geographic object and the address text data of any one ontology library geographic object includes:

[0081] The name matching degree between the non-ontology geographic object and any ontology geographic object in the ontology geographic object set is determined based on the geographic object name data of the non-ontology geographic object and the geographic object name data of any ontology geographic object in the ontology geographic object set.

[0082] Optionally, also include:

[0083] According to the geographical location data of the non-ontology library geographical object and the interest surface data of the any ontology library geographical object, it is determined that the non-ontology library geographical object is located in the interest surface area corresponding to the any ontology library geographical object, to obtain an eleventh determination result;

[0084] Determine whether the non-ontology library geographical object and any one of the ontology library geographical objects are parent-child geographical objects, to obtain a twelfth determination result;

[0085] The determining, based on the address text matching degree and the geographic location matching degree, whether the non-ontology library geographic object and the any one of the ontology library geographic objects are the same geographic object includes: determining, based on the address text matching degree, the geographic location matching degree, the eleventh determination result, and the twelfth determination result, whether the non-ontology library geographic object and the any one of the ontology library geographic objects are the same geographic object.

[0086] Optionally, judging whether the non-ontology library geographical object and any one of the ontology library geographical objects are the same geographical object based on the address text matching degree, the geographical location matching degree, the eleventh judgment result, and the twelfth judgment result includes:

[0087] If the address text matching degree is higher than the address text matching degree threshold, the geographic location matching degree is higher than the geographic location matching degree threshold, the geographic location data of the non-ontology library geographic object is in the key interest surface data of any ontology library geographic object in the ontology library geographic object set, and the non-ontology library geographic object and the any ontology library geographic object are not parent-child geographic objects, then it is determined that the non-ontology library geographic object and the any ontology library geographic object are the same geographic object.

[0088] Optionally, also include:

[0089] If the non-ontology library geographical object and any one of the ontology library geographical objects are not the same geographical object, a plurality of candidate geographical objects having an association relationship with the non-ontology library geographical object are obtained from a preset geographic information system;

[0090] According to the address text matching degree and the geographic location matching degree, determining whether the non-ontology library geographic object and any one of the multiple candidate geographic objects are the same geographic object;

[0091] If the non-ontology library geographical object is the same geographical object as any one of the multiple candidate geographical objects, the mapping relationship between the non-ontology library geographical object and any one of the multiple candidate geographical objects is recorded in the mapping relationship table, and the candidate geographical object data that is the same geographical object as the non-ontology library geographical object is added to the ontology library geographical object set.

[0092] The present application also provides a geographic object processing device, including:

[0093] An obtaining unit, configured to obtain a non-ontology library geographical object and an ontology library geographical object set, wherein the non-ontology library geographical object is a geographical object that does not originate from the ontology library geographical object set;

[0094] a determination unit, configured to determine an address text matching degree and a geographic location matching degree between the non-ontology library geographic object and any ontology library geographic object in the ontology library geographic object set;

[0095] a judgment unit, configured to judge whether the non-ontology library geographical object and any one of the ontology library geographical objects are the same geographical object according to the address text matching degree and the geographical location matching degree;

[0096] The association processing unit is configured to, if yes, associate the non-ontology library geographical object with the ontology library geographical object of the same geographical object in a mapping relationship table.

[0097] The present application also provides an electronic device, which includes a processor and a memory; the memory stores a computer program, and the processor executes the above method after running the computer program.

[0098] The present application also provides a computer storage medium, wherein the computer storage medium stores a computer program, and after the computer program is run by a processor, the above method is executed.

[0099] Compared with the prior art, the embodiments of the present application have the following advantages:

[0100] An embodiment of the present application provides a geographic object processing method, comprising: obtaining a non-ontology library geographic object and an ontology library geographic object set, wherein the non-ontology library geographic object is a geographic object that does not originate from the ontology library geographic object set; determining an address text matching degree and a geographic location matching degree between the non-ontology library geographic object and any one of the ontology library geographic objects in the ontology library geographic object set; judging whether the non-ontology library geographic object and any one of the ontology library geographic objects are the same geographic object based on the address text matching degree and the geographic location matching degree; and if so, associating the non-ontology library geographic object with the ontology library geographic object of the same geographic object in a mapping relationship table.

[0101] The geographic object processing method described in the embodiment of the present application, by utilizing the address text data and geographic location data of the non-ontology library geographic object and any ontology library geographic object in the ontology library geographic object set, can determine whether the non-ontology library geographic object and any ontology library geographic object are the same geographic object based on the address text matching degree and geographic location matching degree between the non-ontology library geographic object and any ontology library geographic object. When the non-ontology library geographic object and any ontology library geographic object are the same geographic object, the geographic object data of the non-ontology library geographic object can be used as supplementary geographic object data of any ontology library geographic object. The geographic object data and the supplementary geographic object data are together used as data for providing geographic object data services to geographic object data demanders. This method improves the mounting rate and mounting accuracy of non-ontology library geographic objects and ontology library geographic objects. BRIEF DESCRIPTION OF THE DRAWINGS

[0102] Figure 1 This is a schematic diagram of a first application scenario of a geographic object processing method provided in the first embodiment of the present application.

[0103] Figure 2 This is a schematic diagram of a second application scenario of a geographic object processing method provided in the first embodiment of the present application.

[0104] Figure 3 This is a schematic diagram of a third application scenario of a geographic object processing method provided in the first embodiment of the present application.

[0105] Figure 4 This is a schematic diagram of a fourth application scenario of a geographic object processing method provided in the first embodiment of the present application.

[0106] Figure 5 This is a flowchart of a geographic object processing method provided in the first embodiment of the present application.

[0107] Figure 6 It is a schematic diagram of a geographic object processing device provided in the second embodiment of the present application.

[0108] Figure 7 This is a schematic diagram of an electronic device provided in the third embodiment of the present application. DETAILED DESCRIPTION

[0109] The following description sets forth many specific details to facilitate a thorough understanding of the present application. However, the present application can be implemented in many other ways than those described herein, and those skilled in the art can make similar generalizations without violating the scope of the present application. Therefore, the present application is not limited to the specific implementations disclosed below.

[0110] First, in order to enable those skilled in the art to better understand the present application solution, the following describes in detail the specific application scenarios of an embodiment of a geographic object processing method provided in the present application.

[0111] Before describing the application scenarios of this geographic object processing method, we first describe the background technology behind it. With the rapid development and increasing maturity of China's real estate industry, it has become a new growth driver for the national economy. House valuation and pricing are prerequisites and foundations for real estate operations and economic accounting. House valuation, also known as real estate valuation, refers to the estimation of a house's value based on factors such as its structure, standards, location, materials, area, and condition. In the field of real estate valuation, real estate valuation models are commonly used to estimate a property's value. Using digital methods to estimate real estate value can improve the accuracy of online real estate valuations. When using a real estate valuation model to estimate a property's value, the characteristic information of the ontology database's neighborhoods (i.e., the geographic object data of the ontology database's geographic objects) is input into the real estate valuation model to obtain a valuation result. Because the characteristic information of the ontology database's neighborhoods is often derived from multiple other housing communities (not the ontology database's neighborhoods), accurate mapping of the ontology database's neighborhoods to the housing communities is crucial for the real estate valuation model. Mounting refers to matching a listing neighborhood to a neighborhood in the ontology database, thereby expanding the neighborhood information in the ontology database. The primary purpose of mounting is to associate neighborhoods in the ontology database with various listing neighborhood information, thereby enriching the ontology database (i.e., enriching the geographic object data of the ontology database's geographic objects), thereby improving the accuracy of the real estate valuation model. Since the addresses of neighborhoods in the ontology database are primarily based on information in the geographic information system (GIS), while the addresses of listing neighborhoods come from a variety of sources and the naming standards for neighborhoods are inconsistent, mounting is more difficult. For example, a neighborhood displayed as "AAXXBB" in the GIS may appear as "AABB" in Listing A and "BB" in Listing B. Furthermore, currently, listings are primarily mounted based on the similarity between the address strings of the listing neighborhood and the ontology database neighborhood, resulting in relatively low mounting accuracy and listing rates.

[0112] Based on this, an embodiment of the present application provides a geographic object processing method. This method utilizes the address text data and geographic location data of a non-ontology library geographic object and any ontology library geographic object in the ontology library geographic object set. Based on the address text matching degree and geographic location matching degree between the non-ontology library geographic object and any ontology library geographic object, it can determine whether the non-ontology library geographic object and any ontology library geographic object are the same geographic object. When the non-ontology library geographic object and any ontology library geographic object are the same geographic object, the geographic object data of the non-ontology library geographic object can be used as supplementary geographic object data of any ontology library geographic object. The geographic object data and the supplementary geographic object data are together used as data for providing geographic object data services to geographic object data demanders. This method improves the mounting rate and mounting accuracy of non-ontology library geographic objects and ontology library geographic objects.

[0113] The following is an explanation of the technical terms involved in the embodiments of this application:

[0114] The ontology database geographic object collection, also known as the ontology database neighborhood collection or neighborhood ontology library, refers to a collection of neighborhoods maintained by a dedicated team. The geographic object data of the ontology database geographic objects includes information such as the neighborhood address and the neighborhood's latitude and longitude coordinates. The richer the neighborhood data in the ontology database, the more accurate the valuation results will be when evaluating the ontology neighborhood using the real estate valuation model.

[0115] Non-ontology database geographic objects, also known as housing communities, refer to third-party communities. The geographic object data for non-ontology database geographic objects includes information such as the address and longitude and latitude coordinates of the housing community.

[0116] Sub-cells and parent cells refer to a cell that may be composed of multiple sub-cells, and this cell is called the parent cell. For example, a parent cell "XX City" has multiple sub-cells "XX City Phase I" and "XX City Phase II".

[0117] Mounting refers to matching a property's neighborhood to a neighborhood in the main database, thereby expanding the neighborhood's information. For example, if the property's neighborhood is named "XX" and the neighborhood in the main database is named "XX Bay," and they are the same neighborhood, mounting will associate "XX" with "XX Bay." It's important to note that to ensure the uniqueness and matching rate of the neighborhoods in the main database, the matching relationship can be one-to-many, meaning that a parent property neighborhood can be associated with multiple child neighborhoods in the main database.

[0118] POI: Point of Interest, refers to the key point of interest information in the address.

[0119] AOI: Area of ​​Interest, refers to the area divided by key points of interest in the address.

[0120] Longitude and Latitude: Latitude and longitude are coordinates representing the location of a point on Earth. Longitude is the angle measured east or west from the prime meridian (0° longitude), ranging from -180° to +180°. Latitude is the angle measured north or south from the equator, ranging from -90° to +90°.

[0121] The following combination Figure 1-Figure 4 The application scenarios of the geographic object processing method provided in the embodiments of the present application are described in detail.

[0122] like Figure 1As shown, it is a schematic diagram of the first application scenario of a geographic object processing method provided by the first embodiment of the present application. Before mounting the housing source community and the entity library community, execute Step 1: Community Address Processing, that is, it is necessary to process the housing source community address and the entity library community address, specifically including structuring the housing source community address and the entity library community address, screening out abnormal addresses in the housing source community address and the entity library community address, calibrating the longitude and latitude of the housing source community, etc. By processing the housing source community address and the entity library community address, it is beneficial to the subsequent matching of the housing source community address and the entity library community address.

[0123] After processing the housing estate address and the database address, execute Step 2: Community Mounting. Please refer to Figure 2 , which is a schematic diagram of the second application scenario of a geographic object processing method provided in the first embodiment of this application. There are four types of cell mounting: the first is an exact match, that is, the property cell name and the entity database cell name completely match, and the geographic distance between the property cell and the entity database cell is within a preset geographic distance threshold.

[0124] The second type is fuzzy matching. During fuzzy matching, first, the POI information of the housing source community and the entity database community needs to be matched, for example, "A Rose Bay Community" and "A Rose Bay", where "A" is the developer name. After removing the developer name "A" and the suffix "Community", the two communities have the same key information "Rose Bay". Second, the suffix information of the housing source community name and the entity database community name needs to be matched, for example, "A Rose Bay" and "Rose Bay" have the same suffix "Rose Bay". Third, the parent-child relationship between the housing source community and the entity database community needs to be restricted to avoid the entity database community being the parent community of the housing source. Fourth, the geographical distance between the housing source community and the entity database community needs to be within the preset geographical distance threshold.

[0125] The third type is distance matching. During distance matching, the geographic distance between the source community and the database community must be sorted (i.e., geo_dis sorting). The geographic distance between the source community and the database community must be within a preset geographic distance threshold. Note that the preset geographic distance threshold for distance matching is relatively small, such as 200 meters, while the geographic distance threshold for precise matching is higher, such as 800 meters. This is because precise matching can already confirm that the two communities are compatible, thus allowing for a wider distance limit. Secondly, the text similarity between the source community and the database community must be sorted (i.e., LCS sorting). The similarity between the name of the source community and the database community must exceed a preset text similarity threshold. For example, the LCS value of the two community names must be greater than 0.7. Furthermore, after satisfying the above two conditions, the parent-child relationship between the source community and the database community must be restricted to prevent the database community from being the parent community of the listing. Fourthly, the geographic distance between the source community and the database community must be within a preset geographic distance threshold.

[0126] The fourth type is POI / AOI spatial relationship matching. First, for the ontology database cells with AOI information, the corner accumulation algorithm is used to ensure that the longitude and latitude of the housing source cell are within the area defined by the ontology database cell. Second, it is necessary to limit the parent-child relationship between the housing source cell and the ontology database cell to avoid the ontology database cell being the parent cell of the housing source. Third, the geographical distance between the housing source cell and the ontology database cell must be within the preset geographical distance threshold range.

[0127] The above are the four matching methods for attaching a housing community to the community in the main library. Then execute Step 3: Add a new community. Please refer to Figure 3 , which is a schematic diagram of the third application scenario of a geographic object processing method provided by the first embodiment of this application. If the housing source area and the ontology database area match, the housing source area and the ontology database area are associated in the mapping relationship table, and the successfully mounted housing source data is marked as "mounted", and the unsuccessfully matched housing source data is marked as "not mounted". Please refer to Figure 4, which is a schematic diagram of the fourth application scenario of a geographic object processing method provided in the first embodiment of this application. A mapping relationship table, also known as a mounting mapping table, is a data table used to record the mapping relationship between the entity library communities and the housing source communities. The mounting mapping table primarily includes fields such as the entity library community ID, the housing source community ID, the mounting time, and the mounting method, with the entity library community ID serving as the primary key. For unmounted housing, the community name keyword query function can be used to search the geographic information system, limiting the returned community type to residential, and using the housing source community name as the keyword to query for information on several related communities. The query results are then matched, specifically by performing a one-to-one match between the queried addresses and the unmounted housing. The specific matching methods can refer to the aforementioned precise matching process, fuzzy matching process, and distance matching process. For example, searching for "XX Garden Community" returns related communities such as "XX Home," "XX Garden," and "XX Garden." Using fuzzy matching, "XX Garden Community" can be matched with the "XX Garden" community. The successfully matched housing source communities can then be added to the mounting mapping table, and the newly added address information for the "XX Garden" community is added to the community entity library.

[0128] The above is a full analysis of the geographic object processing method. On the one hand, by comprehensively utilizing the address text data and geographic location data of the housing source community and the entity library community, it is determined whether the housing source community and the entity library community are the same community. If the housing source community and the entity library community are the same community, the housing source community and the entity library community are mounted, which improves the mounting rate and mounting accuracy of the housing source community and the entity library community. On the other hand, for unmounted housing source communities, the address name keywords of the housing source community can be used to search for multiple related communities related to the keywords in the geographic information system. The address text data and geographic location data of the unmounted housing source community and the related communities are then used to further determine whether the unmounted housing source community and the related communities match, thus achieving the expansion of the mounting results. Therefore, this solution improves the mounting rate and mounting accuracy of housing source communities and the entity library communities, thereby providing accurate and rich data information for the real estate valuation model.

[0129] The present application is described in detail below through multiple embodiments and drawings.

[0130] First embodiment

[0131] The first embodiment of the present application provides a method for processing geographic objects. Figure 5 The geographic object processing method is described in detail.

[0132] Step S501: obtaining non-ontology library geographical objects and an ontology library geographical object set, wherein the non-ontology library geographical objects are geographical objects that do not originate from the ontology library geographical object set.

[0133] This step is used to obtain non-ontology library geographic objects and ontology library geographic object collections.

[0134] Non-ontology database geographic objects are also called housing communities, ontology database geographic objects are also called ontology database communities, and ontology database geographic object collections are also called ontology database community collections, which can also be called community ontology libraries. The ontology database geographic object collections are the geographic object data sources required to provide geographic object data services. For example, the ontology database communities in the ontology database community collection can serve as the data source for a real estate valuation model. The richer the data on the ontology database communities in the ontology database community collection, the more accurate the evaluation results will be when the real estate valuation model is used to evaluate the value of the ontology database communities.

[0135] Step S502: determining the address text matching degree and the geographic location matching degree between the non-ontology library geographic object and any ontology library geographic object in the ontology library geographic object set.

[0136] This step is used to determine the address text matching degree and geographic location matching degree between the non-ontology library geographic object and any ontology library geographic object in the ontology library geographic object set.

[0137] In an embodiment of the present application, determining the address text matching degree and geographic location matching degree between the non-ontology library geographic object and any one ontology library geographic object in the ontology library geographic object set includes: determining the address text matching degree between the non-ontology library geographic object and any one ontology library geographic object in the ontology library geographic object set based on the address text data of the non-ontology library geographic object and the address text data of any one ontology library geographic object in the ontology library geographic object set; and determining the geographic location matching degree between the non-ontology library geographic object and any one ontology library geographic object based on the geographic location data of the non-ontology library geographic object and the geographic location data of the any one ontology library geographic object.

[0138] In specific implementation, the address text matching degree between the non-ontology library geographic object and any one of the ontology library geographic objects in the ontology library geographic object set is determined based on the address text data of the non-ontology library geographic object and the address text data of any one of the ontology library geographic objects, that is, the address text matching degree between the housing community and any one of the ontology library communities is determined.

[0139] Before matching the address text data of the housing source community with the address text data of any ontology library community, the housing source community address and the ontology library community address need to be processed. Specifically, the address text data of the housing source community and the ontology library community address text data can be normalized to obtain the normalized address text data of the housing source community and the ontology library community address text data. When determining the address text matching degree between the non-ontology library geographic object and any ontology library geographic object in the ontology library geographic object set based on the address text data of the non-ontology library geographic object and the address text data of the ontology library geographic object set, the normalized data is specifically used for matching.

[0140] When processing the addresses of housing communities and database communities, the addresses in the housing communities and database communities generally include the following information: (1) regional information, such as province, city, county, and township information; (2) road network information, such as road names, road numbers, road facilities, etc.; (3) detailed community information, such as community name, building number, household number, etc.; (4) non-geographic information, such as supplementary instructions, erroneous input, etc.

[0141] When processing the residential community address of a property and the residential community address in the ontology database, the original address needs to be split into independent semantic elements and the types of these elements must be identified to facilitate subsequent matching of the residential community address of the property with the residential community address in the ontology database. For example, "No. 201, Building 2, XX Community, XX Street, XX District, XX City" can be split into "City: XX City, District: XX District, Road: XX Street, Community Name: XX Community, Building Number: Building 2, House Number: 201." It should be noted that when matching the residential community address of the property and the residential community address in the ontology database, the matching is performed based on the corresponding element type.

[0142] In specific implementations, a pre-set model for identifying unusual neighborhoods in a housing stock can be used to identify these neighborhoods and remove them from the stock. When screening for unusual addresses in the housing stock and the database, a large number of unusual neighborhoods exist within the housing stock. Many neighborhoods cannot be searched on a map, and there are also relatively few available properties, including some non-community properties (e.g., office buildings, commercial areas, and streets). These neighborhoods need to be identified. This identification is done by constructing a machine learning recognition model. The model's input features include "total number of households, number of available properties, green space ratio, road status, total number of houses, and incorrect house type." By inputting these neighborhood features into the machine learning recognition model, it is possible to determine whether the neighborhood is an unusual neighborhood and remove the identified unusual neighborhoods. For abnormal addresses in the community database, the addresses need to be structured. On the one hand, non-community addresses such as squares and parks need to be removed, for example, the non-community address of "XX Square, XX Street, XX District, XX City" needs to be removed; on the other hand, the community information needs to be text processed, for example, special characters in the community need to be removed, for example, "#" needs to be removed from "No. 201, Building 2, #XX Community, XX Street, XX District, XX City".

[0143] In specific implementation, the geographic location matching degree between the non-ontology library geographic object and the any ontology library geographic object is determined based on the geographic location data of the non-ontology library geographic object and the any ontology library geographic object, that is, the geographic location matching degree between the housing community and any ontology library community is determined.

[0144] In an embodiment of the present application, the geographic location data of the non-ontology library geographic object and the geographic location data of any one of the ontology library geographic objects can specifically be longitude and latitude data, that is, longitude and latitude coordinate data, including longitude data and latitude data. Before determining the geographic location matching degree between the non-ontology library geographic object and any one of the ontology library geographic objects based on the geographic location data of the non-ontology library geographic object and the geographic location data of any one of the ontology library geographic objects, it is necessary to calibrate the longitude and latitude of the housing source community and the longitude and latitude of the ontology library community. The reason for calibrating the longitude and latitude of the housing source community is that the longitude and latitude of the housing source may be located at the edge of the community, so it is necessary to calibrate the longitude and latitude of the housing source so that the longitude and latitude are located at the center of the community. The longitude and latitude calibration mainly uses the delivery address of the user in the preset transaction platform to match the housing source address, and takes the median of the longitude and latitude of the same-name community in the preset transaction platform and the community distance within 200m to obtain a new longitude and latitude. For example, the address of a property is "No. 201, Building 2, XX Community, XX Street, XX District, XX City". The property is located on the edge of the community, so the latitude and longitude are also located at the edge of the area, which is 116 degrees east longitude and 39 degrees north latitude. At this time, it is necessary to use the user address in the preset transaction platform. For example, user 1's address is "No. 201, Building 1, XX Community, XX Street, XX District, XX City", and user 2's address is "No. 201, Building 3, XX Community, XX Street, XX District, XX City". Assuming that they are within 200m of the property address, obtain their latitude and longitude data, take the median, and use it as the new latitude and longitude of the property.

[0145] It should be noted that the matching degree in the address text matching degree and the geographic location matching degree can be expressed as a value between 0 and 1. In specific implementations, different value ranges can be pre-set to correspond to different matching results between non-ontology geographic objects and any ontology geographic objects. The higher the matching degree between the non-ontology geographic object and any ontology geographic object, the higher the corresponding value range. If it is a perfect match, the value can be 1.

[0146] Step S503: judging whether the non-ontology library geographical object and any one of the ontology library geographical objects are the same geographical object according to the address text matching degree and the geographical location matching degree.

[0147] This step is used to determine whether the non-ontology library geographic object and any one of the ontology library geographic objects are the same geographic object based on the address text matching degree and the geographic location matching degree, that is, to determine whether the housing source community and any one of the ontology library communities are the same community based on the address text matching degree and the geographic location matching degree.

[0148] The above steps are mainly used to determine whether the non-ontology library geographical object and any ontology library geographical object are the same geographical object based on the address text matching degree and the geographical location matching degree, that is, whether to mount the non-ontology library geographical object with any ontology library geographical object. The following describes how to determine whether the non-ontology library geographical object and any ontology library geographical object are the same geographical object based on the address text matching degree and the geographical location matching degree.

[0149] In the specific implementation, it is assumed that the address text data of the non-ontology library geographic object is , whose longitude and latitude are ; The address text data of the geographic object in the ontology library is , whose longitude and latitude are , and AOI information exists , which is a closed figure surrounded by a series of longitude and latitude coordinates.

[0150] In one embodiment, determining the degree of address text matching between the non-ontology geographic object and any one of the ontology geographic objects in the ontology geographic object set based on the address text data of the non-ontology geographic object and the address text data of the ontology geographic object includes: determining whether the geographic object name data of the non-ontology geographic object is the same as the geographic object name data of any one of the ontology geographic objects in the ontology geographic object set, thereby obtaining a first determination result; and determining the degree of address text matching between the non-ontology geographic object and the any one of the ontology geographic objects based on the geographic location data of the non-ontology geographic object and the geographic location data of the any one of the ontology geographic objects, including: determining geographic distance data between the non-ontology geographic object and the any one of the ontology geographic objects based on the geographic location data of the non-ontology geographic object and the geographic location data of the any one of the ontology geographic objects; determining whether the geographic distance data is less than a first geographic distance data threshold, thereby obtaining a second determination result; and determining the degree of geographic location matching between the non-ontology geographic object and the any one of the ontology geographic objects based on the second determination result. The determining, based on the address text matching degree and the geographic location matching degree, whether the non-ontology library geographic object and the any one of the ontology library geographic objects are the same geographic object includes: if the address text matching degree is higher than an address text matching degree threshold, and the geographic location matching degree is higher than a geographic location matching degree threshold, determining that the non-ontology library geographic object and the any one of the ontology library geographic objects are the same geographic object; and if either the address text matching degree is lower than the address text matching degree threshold, and the geographic location matching degree is lower than the geographic location matching degree threshold, determining that the non-ontology library geographic object and the any one of the ontology library geographic objects are not the same geographic object.

[0151] In specific implementations, the aforementioned method can be used to precisely match a non-ontology geographic object with any ontology geographic object. Precise matching requires, on the one hand, a complete match between the geographic object name data of the non-ontology geographic object and any ontology geographic object. Specifically, when matching the geographic object name data of the non-ontology geographic object with any ontology geographic object, the character strings of the geographic object name data of the non-ontology geographic object and any ontology geographic object are compared. If the character strings of the geographic object name data of the non-ontology geographic object and any ontology geographic object are equal, the geographic object name data of the non-ontology geographic object and any ontology geographic object are identical. Furthermore, the geographic distance data between the non-ontology geographic object and any ontology geographic object must be less than a first geographic distance data threshold. The geographic distance data between the non-ontology geographic object and any ontology geographic object can be calculated using Geographic Information System (GIS) technology. The geographic distance can be approximated using a spherical model, i.e., treating the Earth as a standard ellipsoid and calculating the curvilinear distance between two points on the sphere. In specific implementation, GeoDistanceSortBuilder can be used for sorting, that is, geo_dis sorting. When using geo_dis sorting, you first need to define the index and create a field with the data type geo_point in the index to store the geographic location information. Secondly, you need to query and sort. When querying, use GeoDistanceSortBuilder to specify the sorting geographic location and distance unit (such as kilometers, miles, etc.), and then sort in ascending or descending order based on the distance. Calculate the geographic distance data between non-ontology library geographic objects and any ontology library geographic objects, and set a certain distance threshold , ensuring that the matching non-ontology library geographic objects are within this distance range, i.e. .

[0152] As an embodiment, the determining of the address text matching degree between the non-ontology geographic object and any one of the ontology geographic objects in the ontology geographic object set based on the address text data of the non-ontology geographic object and the address text data of the ontology geographic object includes: determining the point of interest data matching degree between the non-ontology geographic object and any one of the ontology geographic objects in the ontology geographic object set based on the point of interest data of the non-ontology geographic object and the point of interest data of any one of the ontology geographic objects in the ontology geographic object set; determining the name suffix matching degree between the non-ontology geographic object and any one of the ontology geographic objects in the ontology geographic object set based on the geographical object name suffix data of the non-ontology geographic object and the geographical object name suffix data of any one of the ontology geographic objects in the ontology geographic object set; and determining the address text matching degree between the non-ontology geographic object and any one of the ontology geographic objects based on the point of interest data matching degree and the name suffix matching degree.

[0153] During specific implementation, fuzzy matching can also be performed. The fuzzy matching specifically includes address text matching such as POI matching between non-ontology library geographic objects and any ontology library geographic objects, geographic object name suffix data matching between non-ontology library geographic objects and any ontology library geographic objects, the geographic distance between non-ontology library geographic objects and any ontology library geographic objects is within the preset geographic distance threshold range, and the parent-child relationship between non-ontology library geographic objects and any ontology library geographic objects meets the preset requirements.

[0154] The determining of the address text matching degree between the non-ontology library geographic object and the arbitrary ontology library geographic object based on the interest point data matching degree and the name suffix matching degree includes: deleting unnecessary name information in the interest point data of the non-ontology library geographic object to obtain key interest point data of the non-ontology library geographic object; deleting unnecessary name information in the interest point data of the arbitrary ontology library geographic object to obtain key interest point data of the arbitrary ontology library geographic object; judging whether the key interest point data of the non-ontology library geographic object is the same as the key interest point data of the arbitrary ontology library geographic object to obtain a third judgment result; and determining the interest point data matching degree between the non-ontology library geographic object and the arbitrary ontology library geographic object based on the third judgment result.

[0155] When matching POIs, unnecessary name information, such as developer and community information, is removed from the community names of the listing community and any of the communities in the database. POI information for the listing community and any of the communities in the database is extracted separately. Matching is performed if the POI information of the listing community and the community in the database is consistent. For example, "A Rose Bay Community" and "A Rose Bay", where "A" is the developer name, after removing the developer name "A" and the suffix "community", the two communities have the same key information "Rose Bay".

[0156] The method of determining the name suffix matching degree between the non-ontology library geographical object and any one of the ontology library geographical objects in the ontology library geographical object set based on the geographical object name suffix data of the non-ontology library geographical object and the geographical object name suffix data of any one of the ontology library geographical objects includes: determining the string length value of the geographical object name data of the non-ontology library geographical object; determining the string length value of the geographical object name data of any one of the ontology library geographical objects; if the string length value of the geographical object name data of any one of the ontology library geographical objects is less than the string length value of the geographical object name data of the non-ontology library geographical object, then selecting the geographical object name data of the non-ontology library geographical object from the non-ontology library. A character string corresponding to a first character string length difference is truncated from the last character in the geographic object name data of the geographic object as a first truncated character string, wherein the first character string length difference is the difference between the character string length value of the geographic object name data of the non-ontology library geographic object and the character string length value of the geographic object name data of any one of the ontology library geographic objects; a determination is made as to whether the name data corresponding to the first truncated character string is identical to the geographic object name data of any one of the ontology library geographic objects, to obtain a fourth determination result; and a degree of name suffix matching between the non-ontology library geographic object and the any one of the ontology library geographic objects is determined based on the fourth determination result.

[0157] Alternatively, the determining of the name suffix matching degree between the non-ontology library geographical object and any one of the ontology library geographical objects in the ontology library geographical object set based on the geographical object name suffix data of the non-ontology library geographical object and the geographical object name suffix data of any one of the ontology library geographical objects includes: determining the string length value of the geographical object name data of the non-ontology library geographical object; determining the string length value of the geographical object name data of any one of the ontology library geographical objects; if the string length value of the geographical object name data of the non-ontology library geographical object is less than the string length value of the geographical object name data of any one of the ontology library geographical objects, then selecting the geographical object name data of the non-ontology library geographical object from the ontology library geographical object set. A character string corresponding to a second character string length difference is truncated from the last character in the geographic object name data of an ontology library geographic object as a second truncated character string, where the second character string length difference is the difference between the character string length value of the geographic object name data of any ontology library geographic object and the character string length value of the geographic object name data of the non-ontology library geographic object; a determination is made as to whether the name data corresponding to the second truncated character string is identical to the geographic object name data of the non-ontology library geographic object to obtain a fifth determination result; and a degree of name suffix matching between the non-ontology library geographic object and the any ontology library geographic object is determined based on the fifth determination result.

[0158] When matching address texts such as the suffix data of the geographic object name of a non-ontology database geographic object with any ontology database geographic object, a suffix matching algorithm can be used. This suffix-based address matching algorithm ensures that the suffix information of the housing community and the ontology database community is consistent. For example, "A Rose Bay" and "Rose Bay" have the same suffix "Rose Bay". Suffix matching needs to meet the following conditions:

[0159]

[0160] in, The length of the string representing the name of the housing estate. The length of the string representing the cell name in the ontology library. The first character string representing the interception of the housing estate name To Bit.

[0161] In specific implementations, after address text matching, such as matching the POI of a non-ontology database geographic object with any ontology database geographic object and matching the geographic object name suffix data of the non-ontology database geographic object with any ontology database geographic object, it is also necessary to limit the geographic distance between the non-ontology database geographic object and any ontology database geographic object to within a preset geographic distance threshold, and to ensure that the parent-child relationship between the non-ontology database geographic object and any ontology database geographic object meets preset requirements. Therefore, it is also necessary to ensure that the geographic distance between the non-ontology database geographic object and any ontology database geographic object is within the preset geographic distance threshold, and to determine whether the non-ontology database geographic object and the any ontology database geographic object are parent-child geographic objects, thereby obtaining a sixth judgment result.

[0162] In an embodiment of the present application, judging whether the non-ontology library geographic object and any one of the ontology library geographic objects are the same geographic object based on the address text matching degree and the geographic location matching degree includes: judging whether the non-ontology library geographic object and any one of the ontology library geographic objects are the same geographic object based on the address text matching degree, the geographic location matching degree, and the sixth judgment result. The judging whether the non-ontology library geographic object and any one of the ontology library geographic objects are parent-child geographic objects to obtain the sixth judgment result includes: determining a child geographic object of any one of the ontology library geographic objects as an ontology library child geographic object; determining geographic object name data of the ontology library child geographic object; determining a geographic object name matching degree between the geographic object name data of the ontology library child geographic object and the geographic object name data of the non-ontology library geographic object; judging whether the non-ontology library geographic object and any one of the ontology library geographic objects are parent-child geographic objects based on the geographic object name matching degree between the geographic object name data of the ontology library child geographic object and the geographic object name data of the non-ontology library geographic object, thereby obtaining the sixth judgment result.

[0163] In specific implementation, it is necessary to limit the parent-child relationship between the housing district and the ontology database district to avoid the ontology database district being the parent district of the housing district. Assume that the name data of the ontology database sub-geographic object is For example, XX Community Phase I, XX Community Phase II, XX Community Area A, XX Community Area B, etc., the housing community and the main database sub-community must meet the following conditions: .

[0164] The above is the restriction of the parent-child relationship between the housing community and the ontology library community. When it is implemented specifically, it is also necessary to limit the geographical distance between the non-ontology library geographical object and any ontology library geographical object to be within the preset geographical distance threshold range. The geographical location matching degree between the non-ontology library geographical object and any ontology library geographical object is determined based on the geographical location data of the non-ontology library geographical object and the geographical location data of any ontology library geographical object, including: determining the geographical distance data between the non-ontology library geographical object and any ontology library geographical object based on the geographical location data of the non-ontology library geographical object and the geographical location data of any ontology library geographical object; judging whether the geographical distance data is less than a second geographical distance data threshold , obtain the seventh judgment result; according to the seventh judgment result, determine the geographical location matching degree between the non-ontology library geographical object and the any one ontology library geographical object, that is, the distance restriction satisfies .

[0165] In an embodiment of the present application, the determining whether the non-ontology library geographic object and any one of the ontology library geographic objects are the same geographic object based on the address text matching degree, the geographic location matching degree, and the sixth judgment result includes: if the address text matching degree is higher than the address text matching degree threshold, the geographic location matching degree is higher than the geographic location matching degree threshold, and the non-ontology library geographic object and any one of the ontology library geographic objects are not parent-child geographic objects, then determining that the non-ontology library geographic object and any one of the ontology library geographic objects are the same geographic object. If the address text matching degree is lower than the address text matching degree threshold, the geographic location matching degree is lower than the geographic location matching degree threshold, and any one of the following conditions holds true: the non-ontology library geographic object and any one of the ontology library geographic objects are parent-child geographic objects, then determining that the non-ontology library geographic object and any one of the ontology library geographic objects are not the same geographic object.

[0166] During specific implementation, distance matching can also be performed. Specifically, the geographical distance between the non-ontology library geographical object and any ontology library geographical object is within the preset geographical distance threshold range, the address text between the non-ontology library geographical object and any ontology library geographical object matches, and the parent-child relationship between the non-ontology library geographical object and any ontology library geographical object meets the preset requirements.

[0167] The method of determining the address text matching degree between the non-ontology library geographic object and any one of the ontology library geographic objects in the ontology library geographic object set based on the address text data of the non-ontology library geographic object and the address text data of any one of the ontology library geographic objects includes: determining the string length value of the geographic object name data of the non-ontology library geographic object; determining the string length value of the geographic object name data of any one of the ontology library geographic objects; determining the larger string length value between the string length value of the geographic object name data of the non-ontology library geographic object and the string length value of the geographic object name data of any one of the ontology library geographic objects based on the string length value of the geographic object name data of the non-ontology library geographic object and the string length value of the geographic object name data of any one of the ontology library geographic objects as the target string length value; traversing all characters in the string of the geographic object name data of the non-ontology library geographic object and the geographic object name data of any one of the ontology library geographic objects; determining the first substring between the first character in the string corresponding to the geographic object name data of the non-ontology library geographic object and the previous character of the currently traversed character and the first character in the string corresponding to the geographic object name data of any one of the ontology library geographic objects to the previous character of the currently traversed character. Based on the first substring and the second substring, determine the first longest common subsequence length value of the geographical object name data of the non-ontology library geographical object and the geographical object name data of any ontology library geographical object; determine the third substring between the first character in the string corresponding to the geographical object name data of the non-ontology library geographical object and the currently traversed character, and the fourth substring between the first character in the string corresponding to the geographical object name data of any ontology library geographical object and the previous character of the currently traversed character; based on the third substring and the fourth substring, determine the the second longest common subsequence length value of the geographical object name data of the non-ontology library geographical object and the geographical object name data of any one of the ontology library geographical objects; determining the longest common subsequence length value of the common subsequence length between the first longest common subsequence length value and the second longest common subsequence length value as the target longest common subsequence length value; judging whether the ratio of the target longest common subsequence length value to the target string length value is greater than a preset ratio threshold value, to obtain an eighth judgment result; and determining, based on the eighth judgment result, a name matching degree between the non-ontology library geographical object and any one of the ontology library geographical objects in the ontology library geographical object set.

[0168] When matching address text between non-ontology database geographic objects and any ontology database geographic objects, the longest common subsequence sorting algorithm is used to sort the address text of the housing community and the ontology database community by similarity, and the threshold is greater than For example, the LCS value of two cell names is limited to be greater than 0.7. LCS (Longest Common Subsequence) is an algorithm used to find the longest common subsequence between two sequences. In specific implementation, LCS needs to meet the following conditions:

[0169]

[0170] Among them, "max(a,b)" means taking the larger number of a and b. Represents a string consisting of the 1st character to the i-th character of a string. LCS(A,B) is the LCS value of the two strings. The process is calculated recursively until all characters in the string are traversed.

[0171] It should be noted that when calculating the longest common subsequence length value of the geographic object name data of a non-ontology geographic object and any ontology geographic object in the ontology geographic object set, a data table can be first established to record the longest common subsequence length value between character pairs consisting of characters in the string corresponding to the geographic object name data of the non-ontology geographic object and characters in the string corresponding to the geographic object name data of any ontology geographic object. Then, each character in the string corresponding to the geographic object name data of the non-ontology geographic object is compared one by one with all characters in the string corresponding to the geographic object name data of any ontology geographic object. When two characters match, the longest common subsequence length can be updated based on the previous calculation result; if they do not match, the current character is ignored to maintain the existing longest common subsequence length value. By integrating all comparison results, the longest common subsequence length value of the non-ontology string and the ontology string can be obtained.

[0172] In an embodiment of the present application, after the address text data of a non-ontology library geographic object and any ontology library geographic object meet preset conditions, it is also necessary to limit the geographic distance between the non-ontology library geographic object and any ontology library geographic object to be within a preset geographic distance threshold, and the parent-child relationship between the non-ontology library geographic object and any ontology library geographic object must meet preset requirements. Specifically, the ninth judgment result is obtained by determining whether the non-ontology library geographic object and any ontology library geographic object are parent-child geographic objects; and the ninth judgment result is obtained by determining whether the non-ontology library geographic object and any ontology library geographic object are the same geographic object based on the address text matching degree and the geographic location matching degree. The method includes: determining whether the non-ontology library geographic object and any ontology library geographic object are the same geographic object based on the address text matching degree, the geographic location matching degree, and the ninth judgment result. The judgment of whether the non-ontology library geographical object and any one of the ontology library geographical objects are parent-child geographical objects, and obtaining the ninth judgment result, includes: determining the child geographical object of any one of the ontology library geographical objects as the ontology library child geographical object; determining the geographical object name data of the ontology library child geographical object; determining the geographical object name matching degree between the geographical object name data of the ontology library child geographical object and the geographical object name data of the non-ontology library geographical object; judging whether the non-ontology library geographical object and any one of the ontology library geographical objects are parent-child geographical objects based on the geographical object name matching degree between the geographical object name data of the ontology library child geographical object and the geographical object name data of the non-ontology library geographical object, and obtaining the ninth judgment result. It should be noted that the process of judging whether the non-ontology library geographical object and any one of the ontology library geographical objects are parent-child geographical objects is consistent with the judgment process in the previous embodiment, and will not be described in detail here. For details, please refer to the content in the above embodiment.

[0173] When determining whether the geographical distance between a non-ontology library geographical object and any one of the ontology library geographical objects is within a preset geographical distance threshold range, specifically, determining the geographical location matching degree between the non-ontology library geographical object and any one of the ontology library geographical objects based on the geographical location data of the non-ontology library geographical object and the geographical location data of the any one of the ontology library geographical objects includes: determining the geographical distance data between the non-ontology library geographical object and any one of the ontology library geographical objects based on the geographical location data of the non-ontology library geographical object and the geographical location data of the any one of the ontology library geographical objects; determining whether the geographical distance data is less than a third geographical distance data threshold value to obtain a tenth determination result; and determining the geographical location matching degree between the non-ontology library geographical object and any one of the ontology library geographical objects based on the tenth determination result.

[0174] In the embodiment of the present application, the geographical distance between the housing source community and the entity database community is sorted, and the threshold is less than ,Right now It should be noted that, in this embodiment, the threshold value of the distance matching restriction is Relatively small, such as 200m; the threshold of the geographical distance limit in the exact match It is relatively high, such as 800m. This is because the precise matching can basically confirm that the two cells can be mounted, so the distance limit is wider.

[0175] The determining, based on the address text matching degree, the geographic location matching degree, and the ninth judgment result, whether the non-ontology library geographic object and the any one ontology library geographic object are the same geographic object includes: if the address text matching degree is higher than an address text matching degree threshold, the geographic location matching degree is higher than a geographic location matching degree threshold, and the non-ontology library geographic object and the any one ontology library geographic object are not parent-child geographic objects, then determining that the non-ontology library geographic object and the any one ontology library geographic object are the same geographic object.

[0176] As an embodiment, determining the address text matching degree between the non-ontology library geographic object and any one of the ontology library geographic objects in the ontology library geographic object set based on the address text data of the non-ontology library geographic object and the address text data of any one of the ontology library geographic objects in the ontology library geographic object set includes: determining the name matching degree between the non-ontology library geographic object and any one of the ontology library geographic objects in the ontology library geographic object set based on the geographic object name data of the non-ontology library geographic object and the geographic object name data of any one of the ontology library geographic objects in the ontology library geographic object set.

[0177] According to the geographic location data of the non-ontology library geographic object and the interest surface data of the arbitrary ontology library geographic object, it is determined that the non-ontology library geographic object is located in the interest surface area corresponding to the arbitrary ontology library geographic object, and an eleventh determination result is obtained; and it is determined whether the non-ontology library geographic object and the arbitrary ontology library geographic object are parent-child geographic objects, and a twelfth determination result is obtained; and according to the address text matching degree and the geographic location matching degree, it is determined whether the non-ontology library geographic object and the arbitrary ontology library geographic object are the same geographic object, including: according to the address text matching degree, the geographic location matching degree, the eleventh determination result, and the twelfth determination result, it is determined whether the non-ontology library geographic object and the arbitrary ontology library geographic object are the same geographic object. The determining whether the non-ontology geographic object and any one of the ontology geographic objects are the same geographic object based on the address text matching degree, the geographic location matching degree, the eleventh judgment result, and the twelfth judgment result includes: if the address text matching degree is higher than the address text matching degree threshold, the geographic location matching degree is higher than the geographic location matching degree threshold, the geographic location data of the non-ontology geographic object is included in the key interest facet data of any one of the ontology geographic objects in the ontology geographic object set, and the non-ontology geographic object and the any one of the ontology geographic objects are not parent-child geographic objects, then determining that the non-ontology geographic object and the any one of the ontology geographic objects are the same geographic object. If the address text matching degree is lower than the address text matching degree threshold, the geographic location matching degree is lower than the geographic location matching degree threshold, the geographic location data of the non-ontology geographic object is not included in the key interest facet data of any one of the ontology geographic objects in the ontology geographic object set, and any one of the following conditions holds true: then determining that the non-ontology geographic object and the any one of the ontology geographic objects are not the same geographic object.

[0178] During specific implementation, AOI matching can also be performed. AOI matching specifically matches the address text data of a non-ontology library geographic object with any ontology library geographic object. For AOI matching, the geographic distance between the non-ontology library geographic object and any ontology library geographic object is within a preset geographic distance threshold, and the parent-child relationship between the non-ontology library geographic object and any ontology library geographic object meets the preset requirements.

[0179] When determining whether the address text data of a non-ontology library geographic object matches that of any ontology library geographic object, the degree of name matching between the non-ontology library geographic object and any ontology library geographic object in the ontology library geographic object set is determined. The determination of the name matching degree is consistent with the determination process of the name matching degree in the above-mentioned distance matching embodiment, and will not be described in detail here. For details, please refer to the determination process in the above-mentioned embodiment.

[0180] For cells in the Ontology Library with AOI information, a rotation angle accumulation algorithm is used to ensure that the longitude and latitude of the housing cell are within the area defined by the Ontology Library. The rotation angle accumulation algorithm determines whether a point is within a polygon. Starting from a vertex of the polygon, the rotation angle is calculated counterclockwise from the point as the center. The angle is calculated by accumulating the angle of each rotation. If the sum of the angles is 360 degrees, the point is within the polygon.

[0181] For the geographical distance between the non-ontology database geographical object and any ontology database geographical object within the preset geographical distance threshold range, and the parent-child relationship between the non-ontology database geographical object and any ontology database geographical object meets the preset requirements, the parent-child relationship and distance between the housing community and the ontology database are also restricted. The conditions must be met. and .

[0182] The specific process of the parent-child relationship and distance restriction is similar to that in the above embodiment. For details, please refer to the description in the above embodiment and will not be described in detail here.

[0183] The above are the four matching methods for mounting housing communities to the main library communities.

[0184] Step S504: If yes, then the non-ontology library geographical object is associated with the ontology library geographical object of the same geographical object in the mapping relationship table.

[0185] This step is used to associate the non-ontology geographic object with any ontology geographic object in a mapping relationship table when the non-ontology geographic object is the same as any ontology geographic object. In specific implementation, the geographic object data of the non-ontology geographic object can be used as supplementary geographic object data of the ontology geographic object of the same geographic object according to the mapping relationship table. The geographic object data and the supplementary geographic object data are used to provide geographic object data services to geographic object data demanders. The mapping relationship table is a data table used to record the mapping relationship between ontology geographic objects and non-ontology geographic objects.

[0186] The mapping relationship table described in the embodiment of the present application also includes: a judgment method for judging whether the non-ontology library geographic object and any one of the ontology library geographic objects are the same geographic object. For example, the judgment methods mentioned above include: precise matching of the non-ontology library geographic object and any one of the ontology library geographic objects, fuzzy matching of the non-ontology library geographic object and any one of the ontology library geographic objects, distance matching of the non-ontology library geographic object and any one of the ontology library geographic objects, and AOI matching of the non-ontology library geographic object and any one of the ontology library geographic objects. The mapping relationship table can specifically be a mounting mapping table. If the housing source community and the ontology library community match, the housing source community and the ontology library community are associated in the mapping relationship table, and the housing source data that is successfully mounted is marked as "mounted", and the housing source data that is not successfully matched is marked as "unmounted". The mounting mapping table mainly includes fields such as the ontology library community id, housing source community id, mounting time, mounting method, etc., among which the ontology library community id is the primary key.

[0187] In a specific implementation, if the non-ontology library geographic object is not the same geographic object as any one of the ontology library geographic objects, multiple candidate geographic objects associated with the non-ontology library geographic object are obtained from a preset geographic information system; based on the address text matching degree and the geographic location matching degree, it is determined whether the non-ontology library geographic object and any one of the multiple candidate geographic objects are the same geographic object; if the non-ontology library geographic object and any one of the multiple candidate geographic objects are the same geographic object, the mapping relationship between the non-ontology library geographic object and any one of the multiple candidate geographic objects is recorded in the mapping relationship table, and the candidate geographic object data that is the same geographic object as the non-ontology library geographic object is added to the ontology library geographic object set.

[0188] For unlisted properties, you can use the community name keyword query function to search from the geographic information system, limit the returned community type to residential, and use the property community name as a keyword to query several related community information. Then match the query results, specifically, match the address obtained from the query one-to-one with the unlisted properties. The specific matching method can refer to the above-mentioned precise matching process, fuzzy matching process, and distance matching process. For example, by searching for "XX Garden Community", "XX Home", "XX Garden", "XX Garden" and other related communities, "XX Garden Community" can be matched with "XX Garden" community through fuzzy matching. At this time, the successfully matched property community can be added to the mounting mapping table, and the newly added address information "XX Garden" community is added to the community body library.

[0189] In a specific implementation, the geographic object data of the non-ontology library geographic object is used as the supplementary geographic object data of the ontology library geographic object of the same geographic object according to the mapping relationship table, and the geographic object data and the supplementary geographic object data are used as data for providing geographic object data services to geographic object data demanders, including: obtaining the target ontology library geographic object from the mapping relationship table as the geographic object to be evaluated; obtaining the ontology library geographic object data and the supplementary geographic object data of the geographic object to be evaluated from the geographic object database for storing geographic object data; obtaining the geographic object data required for evaluating the resource data of the geographic object to be evaluated from the ontology library geographic object data and the supplementary geographic object data of the geographic object to be evaluated; and evaluating the resource data of the geographic object to be evaluated based on the required geographic object data. It should be noted that the geographic objects in the ontology library can be used to evaluate the resource data of the geographic objects. For example, the value of the ontology library community can be evaluated through a real estate valuation model. The ontology library community in the ontology library community set can be used as the data source of the real estate valuation model. The richer the data in the ontology library community set, the higher the accuracy of the evaluation result when evaluating the value of the ontology library community through the real estate valuation model.

[0190] During specific implementation, another non-ontology library geographical object may also be determined; if it is determined that the another non-ontology library geographical object and the target ontology library geographical object in the ontology library geographical object set are the same geographical object, then any non-ontology library geographical object associated with the target ontology library geographical object is determined according to the mapping relationship table as the target non-ontology library geographical object; and it is judged whether the another non-ontology library geographical object and the target non-ontology library geographical object are the same geographical object; if it is determined that the another non-ontology library geographical object and the target non-ontology library geographical object are the same geographical object, and it is determined that the other non-ontology library geographical object and the other non-ontology library geographical objects associated with the target ontology library geographical object except the target non-ontology library geographical object are the same geographical object, then the target non-ontology library geographical object is associated with the target ontology library geographical object in the mapping relationship table. If it is determined that the other non-ontology library geographical object and the target non-ontology library geographical object are not the same geographical object, then determine whether the target non-ontology library geographical object and the target ontology library geographical object are the same geographical object; if it is determined that the target non-ontology library geographical object and the target ontology library geographical object are not the same geographical object, then delete the association relationship between the target non-ontology library geographical object and the target ontology library geographical object in the mapping relationship table.

[0191] It should be noted that for an already-mounted housing community, if the housing community information changes, for example, if the housing community information was previously written incorrectly and then updated, then based on the updated housing community information, it may be determined that the mounted housing community and the community in the main database are no longer the same community. The previously incorrectly written housing community may have accidentally matched a community in the main database, so the housing community with incorrect information was mounted as the community in the main database, but in fact this mounting relationship was caused by incorrect information. Since the newly added housing community is a new information source, it can help verify whether the originally mounted housing community and the community in the main database should still have a mounting relationship, further ensuring the accuracy of the mounting.

[0192] An embodiment of the present application provides a geographic object processing method, comprising: obtaining a non-ontology library geographic object and an ontology library geographic object set, wherein the non-ontology library geographic object is a geographic object that does not originate from the ontology library geographic object set; determining an address text matching degree and a geographic location matching degree between the non-ontology library geographic object and any one of the ontology library geographic objects in the ontology library geographic object set; judging whether the non-ontology library geographic object and any one of the ontology library geographic objects are the same geographic object based on the address text matching degree and the geographic location matching degree; and if so, associating the non-ontology library geographic object with the ontology library geographic object of the same geographic object in a mapping relationship table.

[0193] The geographic object processing method described in the embodiment of the present application, by utilizing the address text data and geographic location data of the non-ontology library geographic object and any ontology library geographic object in the ontology library geographic object set, can determine whether the non-ontology library geographic object and any ontology library geographic object are the same geographic object based on the address text matching degree and geographic location matching degree between the non-ontology library geographic object and any ontology library geographic object. When the non-ontology library geographic object and any ontology library geographic object are the same geographic object, the geographic object data of the non-ontology library geographic object can be used as supplementary geographic object data of any ontology library geographic object. The geographic object data and the supplementary geographic object data are used as data for providing geographic object data services to geographic object data demanders. This method improves the mounting rate and mounting accuracy of non-ontology library geographic objects and ontology library geographic objects.

[0194] Second embodiment

[0195] In the first embodiment described above, a geographic object processing method is provided. Correspondingly, the second embodiment of the present application provides a geographic object processing device. Since the device embodiment is substantially similar to the first method embodiment, its description is relatively brief. For relevant details, please refer to the description of the method embodiment. The device embodiment described below is merely illustrative.

[0196] Please refer to Figure 6 , is a schematic diagram of a geographic object processing device provided in the second embodiment of the present application.

[0197] The geographic object processing device 600 includes:

[0198] An obtaining unit 601 is configured to obtain a non-ontology library geographical object and an ontology library geographical object set, wherein the non-ontology library geographical object is a geographical object that does not originate from the ontology library geographical object set;

[0199] A determining unit 602 is configured to determine an address text matching degree and a geographic location matching degree between the non-ontology library geographic object and any ontology library geographic object in the ontology library geographic object set;

[0200] A judging unit 603 is configured to judge whether the non-ontology library geographical object and any one of the ontology library geographical objects are the same geographical object according to the address text matching degree and the geographical location matching degree;

[0201] The association processing unit 604 is configured to, if yes, associate the non-ontology library geographic object with the ontology library geographic object of the same geographic object in a mapping relationship table.

[0202] Third embodiment

[0203] Corresponding to the above method embodiment of the present application, the third embodiment of the present application further provides an electronic device. Figure 7 As shown, Figure 7 This is a schematic diagram of an electronic device provided in the third embodiment of the present application. The electronic device includes: at least one processor 701, at least one communication interface 702, at least one memory 703 and at least one communication bus 704; optionally, the communication interface 702 may be an interface of a communication module, such as an interface of a GSM module; the processor 701 may be a processor CPU, or an application-specific integrated circuit ASIC (Application Specific Integrated Circuit), or one or more integrated circuits configured to implement the embodiments of the present invention. The memory 703 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk storage. The memory 703 stores a program, and the processor 701 calls the program stored in the memory 703 to execute the method provided in the above embodiment of the present application.

[0204] Fourth embodiment

[0205] Corresponding to the above method of the present application, the fourth embodiment of the present application further provides a computer storage medium. The computer storage medium stores a computer program, which is executed by a processor to execute the method provided in the above embodiment of the present application.

[0206] Although the present application is disclosed as above with the preferred embodiments, it is not intended to limit the present application. Any person skilled in the art may make possible changes and modifications without departing from the spirit and scope of the present application. Therefore, the scope of protection of the present application shall be based on the scope defined by the claims of the present application.

[0207] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0208] Memory may include non-permanent storage in a computer-readable medium, in the form of random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0209] 1. Computer-readable media, including both permanent and non-permanent, removable and non-removable media, can be implemented using any method or technology to store information. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change RAM (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include non-transitory computer-readable media, such as modulated data signals and carrier waves.

[0210] 2. Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROMs, optical storage, etc.) containing computer-usable program code.

[0211] It should be noted that the embodiments of this application may involve the use of user data. In actual applications, user-specific personal data can be used in the scheme described herein within the scope permitted by applicable laws and regulations, subject to the requirements of applicable laws and regulations of the country where the user is located (for example, with the user's explicit consent, effective notification to the user, etc.).

[0212] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

Claims

1. A geographic object processing method, characterized in that: include: Obtaining a non-ontology library geographic object and an ontology library geographic object set, wherein the non-ontology library geographic object is a geographic object that does not originate from the ontology library geographic object set, wherein the ontology library geographic object set is a geographic object data source required to provide geographic object data services; Determine the address text matching degree and the geographic location matching degree between the non-ontology library geographic object and any ontology library geographic object in the ontology library geographic object set; According to the address text matching degree and the geographic location matching degree, determining whether the non-ontology library geographic object and any one of the ontology library geographic objects are the same geographic object; If so, the non-ontology library geographical object is associated with the ontology library geographical object of the same geographical object in the mapping relationship table, and the geographical object data of the non-ontology library geographical object is used as the supplementary geographical object data of the ontology library geographical object of the same geographical object; A target ontology library geographic object is obtained as the geographic object to be evaluated, and resource data of the geographic object to be evaluated is evaluated based on the ontology library geographic object data and data in the supplementary geographic object data of the geographic object to be evaluated; wherein the geographic object data refers to feature information of the geographic object.

2. The geographic object processing method according to claim 1, characterized in that: The determining of the address text matching degree and the geographic location matching degree between the non-ontology library geographic object and any ontology library geographic object in the ontology library geographic object set includes: Determining an address text matching degree between the non-ontology library geographic object and any one ontology library geographic object in the ontology library geographic object set based on the address text data of the non-ontology library geographic object and the address text data of any one ontology library geographic object in the ontology library geographic object set; The geographical location matching degree between the non-ontology library geographical object and the any ontology library geographical object is determined according to the geographical location data of the non-ontology library geographical object and the geographical location data of the any ontology library geographical object.

3. The geographic object processing method according to claim 2, characterized in that: The determining, based on the address text data of the non-ontology library geographic object and the address text data of any one ontology library geographic object in the ontology library geographic object set, the address text matching degree between the non-ontology library geographic object and the any one ontology library geographic object comprises: Determine whether the geographical object name data of the non-ontology library geographical object is the same as the geographical object name data of any ontology library geographical object in the ontology library geographical object set, and obtain a first determination result; According to the first judgment result, the address text matching degree between the non-ontology library geographical object and the any one ontology library geographical object is determined.

4. The geographic object processing method according to claim 3, characterized in that: The determining, based on the geographical location data of the non-ontology library geographical object and the geographical location data of any one of the ontology library geographical objects, the geographical location matching degree between the non-ontology library geographical object and the any one of the ontology library geographical objects includes: Determining geographical distance data between the non-ontology library geographical object and the any one ontology library geographical object based on the geographical location data of the non-ontology library geographical object and the geographical location data of the any one ontology library geographical object; Determine whether the geographic distance data is less than a first geographic distance data threshold, and obtain a second determination result; According to the second judgment result, a geographical location matching degree between the non-ontology library geographical object and the any one ontology library geographical object is determined.

5. The geographic object processing method according to claim 4, characterized in that: The determining, based on the address text matching degree and the geographic location matching degree, whether the non-ontology library geographic object and any one of the ontology library geographic objects are the same geographic object includes: If the address text matching degree is higher than the address text matching degree threshold, and the geographic location matching degree is higher than the geographic location matching degree threshold, it is determined that the non-ontology library geographic object and the any ontology library geographic object are the same geographic object.

6. The geographic object processing method according to claim 2, characterized in that: The determining, based on the address text data of the non-ontology library geographic object and the address text data of any one ontology library geographic object in the ontology library geographic object set, the address text matching degree between the non-ontology library geographic object and the any one ontology library geographic object comprises: Determining a matching degree of the point of interest data between the non-ontology library geographical object and any one ontology library geographical object in the ontology library geographical object set according to the point of interest data of the non-ontology library geographical object and the point of interest data of any one ontology library geographical object in the ontology library geographical object set; Determining a name suffix matching degree between the non-ontology library geographical object and any one ontology library geographical object in the ontology library geographical object set based on the geographical object name suffix data of the non-ontology library geographical object and the geographical object name suffix data of any one ontology library geographical object in the ontology library geographical object set; The address text matching degree between the non-ontology library geographic object and the any one ontology library geographic object is determined according to the point of interest data matching degree and the name suffix matching degree.

7. The geographic object processing method according to claim 6, characterized in that: The determining, based on the point of interest data matching degree and the name suffix matching degree, the address text matching degree between the non-ontology library geographic object and the any one ontology library geographic object includes: Deleting unnecessary name information in the point of interest data of the non-ontology library geographic object to obtain key point of interest data of the non-ontology library geographic object; Deleting unnecessary name information in the point of interest data of any one of the ontology library geographic objects, and obtaining key point of interest data of any one of the ontology library geographic objects; Determine whether the key point of interest data of the non-ontology library geographic object is the same as the key point of interest data of any one of the ontology library geographic objects to obtain a third determination result; According to the third judgment result, a matching degree of point of interest data between the non-ontology library geographic object and any one of the ontology library geographic objects is determined.

8. The geographic object processing method according to claim 6, characterized in that: The determining, based on the geographical object name suffix data of the non-ontology library geographical object and the geographical object name suffix data of any one of the ontology library geographical objects in the ontology library geographical object set, a name suffix matching degree between the non-ontology library geographical object and the any one of the ontology library geographical objects comprises: Determine the character string length value of the geographic object name data of the non-ontology library geographic object; Determine the character string length value of the geographic object name data of any geographic object in the ontology library; If the character string length value of the geographic object name data of any ontology library geographic object is less than the character string length value of the geographic object name data of the non-ontology library geographic object, then truncating a character string corresponding to a first character string length difference from the last character of the geographic object name data of the non-ontology library geographic object forward as a first truncated character string, wherein the first character string length difference is the difference between the character string length value of the geographic object name data of the non-ontology library geographic object and the character string length value of the geographic object name data of any ontology library geographic object; determining whether the name data corresponding to the first intercepted character string is identical to the geographic object name data of any geographic object in the ontology library, to obtain a fourth determination result; According to the fourth judgment result, a name suffix matching degree between the non-ontology library geographical object and the any one ontology library geographical object is determined.

9. The geographic object processing method according to claim 6, characterized in that: The determining, based on the geographical object name suffix data of the non-ontology library geographical object and the geographical object name suffix data of any one of the ontology library geographical objects in the ontology library geographical object set, a name suffix matching degree between the non-ontology library geographical object and the any one of the ontology library geographical objects comprises: Determine the character string length value of the geographic object name data of the non-ontology library geographic object; Determine the character string length value of the geographic object name data of any geographic object in the ontology library; If the character string length value of the geographic object name data of the non-ontology library geographic object is less than the character string length value of the geographic object name data of any one of the ontology library geographic objects, then truncating a character string corresponding to a second character string length difference from the last character of the geographic object name data of any one of the ontology library geographic objects as a second truncated character string, wherein the second character string length difference is the difference between the character string length value of the geographic object name data of any one of the ontology library geographic objects and the character string length value of the geographic object name data of the non-ontology library geographic object; determining whether the name data corresponding to the second intercepted character string is identical to the geographic object name data of the non-ontology library geographic object, to obtain a fifth determination result; According to the fifth judgment result, a name suffix matching degree between the non-ontology library geographical object and the any one ontology library geographical object is determined.

10. The geographic object processing method according to claim 6, characterized in that: Also includes: Determine whether the non-ontology library geographical object and any one of the ontology library geographical objects are parent-child geographical objects, to obtain a sixth determination result; The determining, based on the address text matching degree and the geographic location matching degree, whether the non-ontology library geographic object and any one of the ontology library geographic objects are the same geographic object includes: determining, based on the address text matching degree, the geographic location matching degree, and the sixth determination result, whether the non-ontology library geographic object and any one of the ontology library geographic objects are the same geographic object.

11. The geographic object processing method according to claim 10, characterized in that: The determining whether the non-ontology library geographical object and any one of the ontology library geographical objects are parent-child geographical objects to obtain a sixth determination result includes: Determine a sub-geographical object of any ontology library geographic object as the ontology library sub-geographical object; Determine the geographic object name data of the ontology library sub-geographic object; Determine a geographic object name matching degree between the geographic object name data of the ontology library sub-geographic object and the geographic object name data of the non-ontology library geographic object; According to the geographic object name matching degree between the geographic object name data of the ontology library child geographic object and the geographic object name data of the non-ontology library geographic object, it is determined whether the non-ontology library geographic object and any one of the ontology library geographic objects are parent-child geographic objects to obtain the sixth judgment result.

12. The geographic object processing method according to claim 10, characterized in that: The determining, based on the address text matching degree, the geographic location matching degree, and the sixth determination result, whether the non-ontology library geographic object and any one of the ontology library geographic objects are the same geographic object includes: If the address text matching degree is higher than the address text matching degree threshold, the geographic location matching degree is higher than the geographic location matching degree threshold, and the non-ontology library geographic object and any one of the ontology library geographic objects are not parent-child geographic objects, then it is determined that the non-ontology library geographic object and any one of the ontology library geographic objects are the same geographic object.

13. The geographic object processing method according to claim 6, characterized in that: The determining, based on the geographical location data of the non-ontology library geographical object and the geographical location data of any one of the ontology library geographical objects, the geographical location matching degree between the non-ontology library geographical object and the any one of the ontology library geographical objects includes: Determining geographical distance data between the non-ontology library geographical object and the any one ontology library geographical object based on the geographical location data of the non-ontology library geographical object and the geographical location data of the any one ontology library geographical object; Determine whether the geographic distance data is less than a second geographic distance data threshold to obtain a seventh determination result; According to the seventh judgment result, a geographical location matching degree between the non-ontology library geographical object and any one of the ontology library geographical objects is determined.

14. The geographic object processing method according to claim 2, characterized in that: The determining, based on the address text data of the non-ontology library geographic object and the address text data of any one ontology library geographic object in the ontology library geographic object set, the address text matching degree between the non-ontology library geographic object and the any one ontology library geographic object comprises: Determine the character string length value of the geographic object name data of the non-ontology library geographic object; Determine the character string length value of the geographic object name data of any geographic object in the ontology library; According to the character string length value of the geographical object name data of the non-ontology library geographical object and the character string length value of the geographical object name data of any one of the ontology library geographical objects, determining the larger character string length value between the character string length value of the geographical object name data of the non-ontology library geographical object and the character string length value of the geographical object name data of any one of the ontology library geographical objects as the target character string length value; Traverse all characters in the character string of the geographical object name data of the non-ontology library geographical object and the geographical object name data of any one of the ontology library geographical objects; Determine a first substring between the first character in the character string corresponding to the geographic object name data of the non-ontology library geographic object and the character preceding the currently traversed character, and a second substring between the first character in the character string corresponding to the geographic object name data of any ontology library geographic object and the currently traversed character; Determine, based on the first substring and the second substring, a first longest common subsequence length value between the geographic object name data of the non-ontology library geographic object and the geographic object name data of any one of the ontology library geographic objects; Determine a third substring between the first character in the character string corresponding to the geographic object name data of the non-ontology library geographic object and the currently traversed character, and a fourth substring between the first character in the character string corresponding to the geographic object name data of any ontology library geographic object and the character immediately preceding the currently traversed character; Determine, based on the third substring and the fourth substring, a second longest common subsequence length value between the geographic object name data of the non-ontology library geographic object and the geographic object name data of any one of the ontology library geographic objects; Determine a longest common subsequence length value between the first longest common subsequence length value and the second longest common subsequence length value as a target longest common subsequence length value; Determine whether a ratio of the target longest common subsequence length to the target character string length is greater than a preset ratio threshold, to obtain an eighth determination result; According to the eighth judgment result, a name matching degree between the non-ontology library geographical object and any ontology library geographical object in the ontology library geographical object set is determined.

15. The geographic object processing method according to claim 14, characterized in that: Also includes: Determine whether the non-ontology library geographical object and any one of the ontology library geographical objects are parent-child geographical objects, to obtain a ninth determination result; The determining, based on the address text matching degree and the geographic location matching degree, whether the non-ontology library geographic object and any one of the ontology library geographic objects are the same geographic object includes: determining, based on the address text matching degree, the geographic location matching degree and the ninth judgment result, whether the non-ontology library geographic object and any one of the ontology library geographic objects are the same geographic object.

16. The geographic object processing method according to claim 15, characterized in that: The determining whether the non-ontology library geographical object and any one of the ontology library geographical objects are parent-child geographical objects, to obtain a ninth determination result, includes: Determine a sub-geographical object of any ontology library geographic object as the ontology library sub-geographical object; Determine the geographic object name data of the ontology library sub-geographic object; Determine a geographic object name matching degree between the geographic object name data of the ontology library sub-geographic object and the geographic object name data of the non-ontology library geographic object; According to the geographic object name matching degree between the geographic object name data of the ontology library child geographic object and the geographic object name data of the non-ontology library geographic object, it is determined whether the non-ontology library geographic object and any one of the ontology library geographic objects are parent-child geographic objects to obtain the ninth judgment result.

17. The geographic object processing method according to claim 15, characterized in that: The determining, based on the address text matching degree, the geographic location matching degree, and the ninth judgment result, whether the non-ontology library geographic object and any one of the ontology library geographic objects are the same geographic object includes: If the address text matching degree is higher than the address text matching degree threshold, the geographic location matching degree is higher than the geographic location matching degree threshold, and the non-ontology library geographic object and any one of the ontology library geographic objects are not parent-child geographic objects, then it is determined that the non-ontology library geographic object and any one of the ontology library geographic objects are the same geographic object.

18. The geographic object processing method according to claim 14, characterized in that: The determining, based on the geographical location data of the non-ontology library geographical object and the geographical location data of any one of the ontology library geographical objects, the geographical location matching degree between the non-ontology library geographical object and the any one of the ontology library geographical objects includes: Determining geographical distance data between the non-ontology library geographical object and the any one ontology library geographical object based on the geographical location data of the non-ontology library geographical object and the geographical location data of the any one ontology library geographical object; Determine whether the geographic distance data is less than a third geographic distance data threshold, to obtain a tenth determination result; According to the tenth judgment result, a geographical location matching degree between the non-ontology library geographical object and any one of the ontology library geographical objects is determined.

19. The geographic object processing method according to claim 2, characterized in that: The determining, based on the address text data of the non-ontology library geographic object and the address text data of any one ontology library geographic object in the ontology library geographic object set, the address text matching degree between the non-ontology library geographic object and the any one ontology library geographic object comprises: The name matching degree between the non-ontology geographic object and any ontology geographic object in the ontology geographic object set is determined based on the geographic object name data of the non-ontology geographic object and the geographic object name data of any ontology geographic object in the ontology geographic object set.

20. The geographic object processing method according to claim 19, characterized in that: Also includes: According to the geographical location data of the non-ontology library geographical object and the interest surface data of the any ontology library geographical object, it is determined that the non-ontology library geographical object is located in the interest surface area corresponding to the any ontology library geographical object, to obtain an eleventh determination result; Determine whether the non-ontology library geographical object and any one of the ontology library geographical objects are parent-child geographical objects, to obtain a twelfth determination result; The determining, based on the address text matching degree and the geographic location matching degree, whether the non-ontology library geographic object and the any one of the ontology library geographic objects are the same geographic object includes: determining, based on the address text matching degree, the geographic location matching degree, the eleventh determination result, and the twelfth determination result, whether the non-ontology library geographic object and the any one of the ontology library geographic objects are the same geographic object.

21. The geographic object processing method according to claim 20, characterized in that: The determining, based on the address text matching degree, the geographic location matching degree, the eleventh judgment result, and the twelfth judgment result, whether the non-ontology library geographic object and any one of the ontology library geographic objects are the same geographic object includes: If the address text matching degree is higher than the address text matching degree threshold, the geographic location matching degree is higher than the geographic location matching degree threshold, the geographic location data of the non-ontology library geographic object is in the key interest surface data of any ontology library geographic object in the ontology library geographic object set, and the non-ontology library geographic object and the any ontology library geographic object are not parent-child geographic objects, then it is determined that the non-ontology library geographic object and the any ontology library geographic object are the same geographic object.

22. The geographic object processing method according to claim 1, characterized in that: Also includes: If the non-ontology library geographical object and any one of the ontology library geographical objects are not the same geographical object, a plurality of candidate geographical objects having an association relationship with the non-ontology library geographical object are obtained from a preset geographic information system; According to the address text matching degree and the geographic location matching degree, determining whether the non-ontology library geographic object and any one of the multiple candidate geographic objects are the same geographic object; If the non-ontology library geographical object is the same geographical object as any one of the multiple candidate geographical objects, the mapping relationship between the non-ontology library geographical object and any one of the multiple candidate geographical objects is recorded in the mapping relationship table, and the candidate geographical object data that is the same geographical object as the non-ontology library geographical object is added to the ontology library geographical object set.

23. A geographic object processing device, characterized in that: include: an obtaining unit, configured to obtain a non-ontology library geographic object and an ontology library geographic object set, wherein the non-ontology library geographic object is a geographic object that does not originate from the ontology library geographic object set, wherein the ontology library geographic object set is a geographic object data source required for providing geographic object data services; a determination unit, configured to determine an address text matching degree and a geographic location matching degree between the non-ontology library geographic object and any ontology library geographic object in the ontology library geographic object set; a judgment unit, configured to judge whether the non-ontology library geographical object and any one of the ontology library geographical objects are the same geographical object according to the address text matching degree and the geographical location matching degree; an association processing unit, configured to, if yes, associate the non-ontology library geographical object with the ontology library geographical object of the same geographical object in a mapping relationship table, and use the geographical object data of the non-ontology library geographical object as the supplementary geographical object data of the ontology library geographical object of the same geographical object; A target ontology library geographic object is obtained as the geographic object to be evaluated, and resource data of the geographic object to be evaluated is evaluated based on the ontology library geographic object data and data in the supplementary geographic object data of the geographic object to be evaluated; wherein the geographic object data refers to feature information of the geographic object.

24. An electronic device, characterized in that: The electronic device includes a processor and a memory; The memory stores a computer program, and after the processor runs the computer program, it executes the method according to any one of claims 1 to 22.

25. A computer storage medium, characterized in that The computer storage medium stores a computer program, and after the computer program is run by the processor, the method according to any one of claims 1 to 22 is executed.

Images