Geographic object data processing method and device

Abstract

The invention discloses a geographic object data processing method and device, electronic equipment and a computer storage medium. The method comprises the steps of obtaining a non-ontology library geographic object; determining geographic position data of a geographic object of a non-ontology library; based on the geographic position data of the non-ontology library geographic object, determining a geographic space grid where the non-ontology library geographic object is located, and taking the geographic space grid as a target geographic space grid; according to a preset grid object mapping table, determining any ontology library geographic object in the target geographic space grid as a first target ontology library geographic object; judging whether the non-ontology library geographic object and the first target ontology library geographic object are the same geographic object or not according to the geographic position data of the non-ontology library geographic object and the geographic position data of the first target ontology library geographic object; and if yes, taking the geographic object data of the non-ontology library geographic object as supplementary geographic object data of the first target ontology library geographic object.

Description

Technical Field

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

[0002] With the rapid development of the real estate industry, real estate transactions are becoming more frequent, and real estate valuation is particularly important in the real estate transaction process. House valuation, also known as real estate valuation, refers to the estimation of the value of a house based on factors such as its structure, standard, geographical location, materials, area, and age.

[0003] In the scenario of real estate valuation, a real estate valuation model is usually used to estimate the value of the real estate. Estimating the value of the real estate in a digital form can improve the accuracy of online real estate value assessment. When using the real estate valuation model to estimate the value of the real estate, the community data in the community database is specifically input into the real estate valuation model to obtain the valuation result of the real estate. Therefore, the integrity and accuracy of the community data in the community database have an important impact on the accuracy of the real estate valuation results. At present, the community data in the community database comes from various channels, such as online searches, delivery addresses in user historical transaction records, etc. However, the naming of traditional community data is confusing, and different users do not name the same community in a unified manner. The inconsistency of multi-source community data and the quality of community data seriously affect the accuracy of valuation.

[0004] Therefore, how to improve the consistency and quality of cell data in the cell database is a problem that needs to be solved urgently. Summary of the invention

[0005] The embodiment of the present application provides a method for processing geographic object data, which improves the consistency of geographic object data in a geographic object set in an ontology library.

[0006] The embodiment of the present application provides a method for processing geographic object data, including: obtaining a non-ontology library geographic object, wherein the non-ontology library geographic object is a geographic object that does not originate from an ontology library geographic object set; determining geographic location data of the non-ontology library geographic object; based on the geographic location data of the non-ontology library geographic object, determining a geographic space grid where the non-ontology library geographic object is located as a target geographic space grid; according to a pre-set grid object mapping table, determining any one ontology library geographic object in the target geographic space grid as a first target ontology library geographic object, wherein the grid object mapping table records a mapping relationship between a geographic space grid and an ontology library geographic object; according to the geographic location data of the non-ontology library geographic object and the geographic location data of the first target ontology library geographic object, determining whether the non-ontology library geographic object and the first target ontology library geographic object are the same geographic object; if so, using the geographic object data of the non-ontology library geographic object as the supplementary geographic object data of the first target ontology library geographic object.

[0007] Optionally, judging whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object according to the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object includes: Determining a geographic location match between the non-ontology library geographic object and the first target ontology library geographic object according to the geographic location data of the non-ontology library geographic object and the geographic location data of the first target ontology library geographic object; According to the geographical location matching degree, it is determined whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object.

[0008] Optionally, the determining the geographic location matching degree between the non-ontology library geographic object and the first target ontology library geographic object includes: Determine the geographical distance data between the non-ontology library geographical object and the first target ontology library geographical object according to the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object; Determine whether the geographic distance data is less than a first geographic distance data threshold, and obtain a first determination result; According to the first judgment result, the geographical location matching degree between the non-ontology library geographical object and the first target ontology library geographical object is determined.

[0009] Optionally, also include: Determine whether the non-ontology library geographical object and the first target ontology library geographical object are parent-child geographical objects to obtain a second determination result; The step of judging whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object according to the geographical location matching degree includes: According to the geographical location matching degree and the second judgment result, it is determined whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object.

[0010] Optionally, the determining whether the non-ontology library geographical object and the first target ontology library geographical object are parent-child geographical objects to obtain a second determination result includes: Determine a sub-geographical object of the first target 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 the 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 the first target ontology library geographic object are parent-child geographic objects to obtain the second determination result.

[0011] Optionally, judging whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object according to the geographical location matching degree and the second judgment result includes: If the geographic location matching degree is higher than the geographic location matching degree threshold, and the non-ontology library geographic object and the first target ontology library geographic object are not parent-child geographic objects, it is determined that the non-ontology library geographic object and the first target ontology library geographic object are the same geographic object.

[0012] Optionally, also include: Determine the address text data of the non-ontology library geographic object and the address text data of the first target ontology library geographic object; Determining the address text matching degree between the non-ontology library geographical object and the first target ontology library geographical object according to the address text data of the non-ontology library geographical object and the address text data of the first target ontology library geographical object; The determining, based on the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object, whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object comprises: According to the geographic location data of the non-ontology library geographic object and the geographic location data of the first target ontology library geographic object and the address text matching degree between the non-ontology library geographic object and the first target ontology library geographic object, it is determined whether the non-ontology library geographic object and the first target ontology library geographic object are the same geographic object.

[0013] Optionally, determining the address text matching degree between the non-ontology library geographical object and the first target ontology library geographical object according to the address text data of the non-ontology library geographical object and the address text data of the first target ontology library geographical object includes: Determine whether the geographical object name data of the non-ontology library geographical object is the same as the geographical object name data of the first target ontology library geographical object, and obtain a third determination result; According to the third judgment result, the address text matching degree between the non-ontology library geographical object and the first target ontology library geographical object is determined.

[0014] Optionally, judging whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object according to the geographical location matching degree includes: Determine the geographical distance data between the non-ontology library geographical object and the first target ontology library geographical object according to the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object; Determine whether the geographic distance data is less than a second geographic distance data threshold to obtain a fourth determination result; According to the fourth judgment result, the geographical location matching degree between the non-ontology library geographical object and the first target ontology library geographical object is determined.

[0015] Optionally, judging whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object according to the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object and the address text matching degree between the non-ontology library geographical object and the first target ontology library geographical 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 any one of the ontology library geographic objects are the same geographic object.

[0016] Optionally, determining the address text matching degree between the non-ontology library geographical object and the first target ontology library geographical object according to the address text data of the non-ontology library geographical object and the address text data of the first target ontology library geographical object includes: The name matching degree between the non-ontology library geographical object and the first target ontology library geographical object is determined according to the geographical object name data of the non-ontology library geographical object and the geographical object name data of the first target ontology library geographical object.

[0017] Optionally, determining the name matching degree between the non-ontology library geographical object and the first target ontology library geographical object according to the geographical object name data of the non-ontology library geographical object and the geographical object name data of the first target ontology library geographical object includes: Determine a first vector of geographic object name data of the non-ontology library geographic object; Determine a second vector of geographic object name data of the geographic object in the first target ontology library; Determine whether the similarity between the first vector and the second vector is greater than a preset vector similarity threshold, to obtain a fifth determination result; According to the fifth judgment result, the name matching degree between the non-ontology library geographical object and the first target ontology library geographical object is determined.

[0018] Optionally, the determining the geographic location matching degree between the non-ontology library geographic object and the first target ontology library geographic object includes: Determine the geographical distance data between the non-ontology library geographical object and the first target ontology library geographical object according to the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object; Determine whether the geographic distance data is less than a third geographic distance data threshold to obtain a sixth determination result; According to the sixth judgment result, the geographical location matching degree between the non-ontology library geographical object and the first target ontology library geographical object is determined.

[0019] Optionally, also include: Determine whether the non-ontology library geographical object and the first target ontology library geographical object are parent-child geographical objects to obtain a seventh determination result; The determining, based on the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object and the address text matching degree between the non-ontology library geographical object and the first target ontology library geographical object, whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object comprises: Based on the geographic location data of the non-ontology library geographic object and the geographic location data of the first target ontology library geographic object, the address text matching degree between the non-ontology library geographic object and the first target ontology library geographic object, and the seventh judgment result, it is determined whether the non-ontology library geographic object and the first target ontology library geographic object are the same geographic object.

[0020] Optionally, the determining whether the non-ontology library geographical object and the first target ontology library geographical object are parent-child geographical objects to obtain a seventh determination result includes: Determine a sub-geographical object of the first target 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 the 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 the first target ontology library geographic object are parent-child geographic objects to obtain the seventh determination result.

[0021] Optionally, judging whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object according to the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object, the address text matching degree between the non-ontology library geographical object and the first target ontology library geographical object, and the seventh 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 the first target ontology library geographic object 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.

[0022] Optionally, also include: If the non-ontology library geographical object and the first target ontology library geographical object are not the same geographical object, then determining any ontology library geographical object in the target geographic spatial grid except the first target ontology library geographical object as the second target ontology library geographical object; According to the geographical location data of the non-ontology library geographical object and the geographical location data of the second target ontology library geographical object, determining whether the non-ontology library geographical object and the second target ontology library geographical object are the same geographical object; If not, traverse any other ontology library geographic object in the target geographic spatial grid except the first target ontology library geographic object and the second target ontology library geographic object again until the non-ontology library geographic object is the same as any other ontology library geographic object.

[0023] Optionally, after obtaining the non-ontology library geographic object, the method further includes: According to a preset geographical object name prefix and suffix keyword data table, determining whether there is data matching the geographical object name prefix and suffix keywords in the name data of the non-ontology library geographical object; If yes, then a removal process is performed on the non-ontology library geographic objects; Alternatively, according to a preset abnormal data type data table, determining whether the type to which the non-ontology library geographic object belongs is an abnormal data type; If so, a removal process is performed on the non-ontology library geographic objects.

[0024] Optionally, the using the geographical object data of the non-ontology library geographical object as the supplementary geographical object data of the first target ontology library geographical object includes: Obtaining a first target ontology library geographic object as the geographic object to be evaluated; Obtaining the target ontology library geographic object data and supplementary geographic object data of the geographic object to be evaluated from a geographic object database for storing geographic object data; Obtaining geographic object data required for evaluating resource data of the geographic object to be evaluated from the target ontology library geographic object data and the supplementary geographic object data of the geographic object to be evaluated; The resource data of the to-be-evaluated geographical object is evaluated according to the required geographical object data.

[0025] The present application also provides a geographic object data processing device, including: A non-ontology library geographical object obtaining unit, used to obtain a non-ontology library geographical object, wherein the non-ontology library geographical object is a geographical object that does not originate from the ontology library geographical object set; A geographical location data determining unit, used to determine the geographical location data of the non-ontology library geographical object; A target geospatial grid determination unit, configured to determine, based on the geographical location data of the non-ontology library geographical object, the geospatial grid where the non-ontology library geographical object is located as the target geospatial grid; A first target ontology library geographic object determination unit, configured to determine any ontology library geographic object in the target geographic spatial grid as the first target ontology library geographic object according to a preset grid object mapping table, wherein the grid object mapping table records a mapping relationship between the geographic spatial grid and the ontology library geographic object; A judging unit, configured to judge whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object according to the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object; The supplementary geographic object data obtaining unit is used to use the geographic object data of the non-ontology library geographic object as the supplementary geographic object data of the first target ontology library geographic object.

[0026] The present application also provides an electronic device, which includes a processor and a memory; a computer program is stored in the memory, and the processor executes the above method after running the computer program.

[0027] 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.

[0028] Compared with the prior art, the embodiments of the present application have the following advantages: The embodiment of the present application provides a method for processing geographic object data, including: obtaining a non-ontology library geographic object, wherein the non-ontology library geographic object is a geographic object that does not originate from an ontology library geographic object set; determining geographic location data of the non-ontology library geographic object; based on the geographic location data of the non-ontology library geographic object, determining a geographic space grid where the non-ontology library geographic object is located as a target geographic space grid; according to a pre-set grid object mapping table, determining any one ontology library geographic object in the target geographic space grid as a first target ontology library geographic object, wherein the grid object mapping table records a mapping relationship between a geographic space grid and an ontology library geographic object; according to the geographic location data of the non-ontology library geographic object and the geographic location data of the target ontology library geographic object, determining whether the non-ontology library geographic object and the first target ontology library geographic object are the same geographic object; if so, using the geographic object data of the non-ontology library geographic object as the supplementary geographic object data of the first target ontology library geographic object.

[0029] The geographic object data processing method described in the embodiment of the present application can determine the geographic space grid where the non-ontology library geographic object is located based on the geographic location data of the non-ontology library geographic object that is not derived from the ontology library geographic object set, and then determine any ontology library geographic object (first target ontology library geographic object) in the geographic space grid where the non-ontology library geographic object is located according to the pre-set grid object mapping table. Finally, based on the geographic location data of the non-ontology library geographic object and the geographic location data of the first target ontology library geographic object, it is determined whether the two are the same geographic object. If so, the geographic object data of the non-ontology library geographic object is used as the supplementary geographic object data of the first target ontology library geographic object, and the geographic object data and the supplementary geographic object data are used together as data for providing geographic object data services to the geographic object data demander. The geographic object data processing method improves the consistency of geographic object data in the ontology library geographic object set. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 It is a schematic diagram of a first application scenario of a geographic object data processing method provided in the first embodiment of the present application.

[0031] Figure 2 It is a schematic diagram of a second application scenario of a geographic object data processing method provided in the first embodiment of the present application.

[0032] Figure 3 It is a schematic diagram of a third application scenario of a geographic object data processing method provided in the first embodiment of the present application.

[0033] Figure 4 It is a schematic diagram of the fourth application scenario of a geographic object data processing method provided in the first embodiment of the present application.

[0034] Figure 5 It is a schematic diagram of the fifth application scenario of a geographic object data processing method provided in the first embodiment of the present application.

[0035] Figure 6 It is a schematic diagram of the sixth application scenario of a geographic object data processing method provided in the first embodiment of the present application.

[0036] Figure 7 It is a flowchart of a geographic object data processing method provided in the first embodiment of the present application.

[0037] Figure 8 It is a schematic diagram of a geographic object data processing device provided in the second embodiment of the present application.

[0038] Fig. 9 This is a schematic diagram of an electronic device provided in the third embodiment of the present application. DETAILED DESCRIPTION

[0039] Many specific details are described in the following description to facilitate a full 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 connotation of the present application, so the present application is not limited by the specific implementation disclosed below.

[0040] First, in order to enable those skilled in the art to better understand the present application, a specific application scenario of an embodiment of the present application is described in detail below based on a geographic object data processing method provided in the present application.

[0041] Before describing the specific application scenarios of the embodiments of the present application in detail, the background of the scheme is first described. With the rapid development of the real estate industry, real estate transactions are becoming more and more frequent, and real estate valuation in the real estate transaction process is particularly important. House valuation, also known as real estate valuation, refers to the estimation of the value of a house based on factors such as the structure, standard, geographical location, materials, area, and newness of the house. In the scenario of real estate valuation, a real estate valuation model is usually used to estimate the value of the house. Estimating the value of the house in a digital form can improve the accuracy of online real estate value assessment. When estimating the value of the house using the real estate valuation model, the cell data in the cell database is specifically input into the real estate valuation model to obtain the valuation result of the house. Therefore, the integrity and accuracy of the cell data in the cell database have an important impact on the accuracy of the real estate valuation result. At present, the cell data in the cell database comes from a variety of channels, such as network searches, delivery addresses in user historical transaction records, etc. However, the naming of traditional cell data is confusing, and different users do not name the same cell uniformly. The inconsistency of multi-source cell data and the quality of cell data seriously affect the accuracy of the valuation.

[0042] Based on this, an embodiment of the present application provides a geographic object data processing method, which can determine the geographic space grid where the non-ontology library geographic object is located based on the geographic location data of the non-ontology library geographic object that is not derived from the ontology library geographic object set, and then determine any ontology library geographic object (first target ontology library geographic object) in the geographic space grid where the non-ontology library geographic object is located according to the pre-set grid object mapping table. Finally, based on the geographic location data of the non-ontology library geographic object and the geographic location data of the first target ontology library geographic object, it is determined whether the two are the same geographic object. If so, the geographic object data of the non-ontology library geographic object is used as the supplementary geographic object data of the first target ontology library geographic object, and the geographic object data and the supplementary geographic object data are used together as data for providing geographic object data services to the geographic object data demander. This geographic object data processing method improves the consistency of geographic object data in the ontology library geographic object set.

[0043] The following is an explanation of the technical terms involved in the embodiments of the present application: The ontology library geographic object collection, also known as the ontology library community collection, or community ontology library, refers to a community collection maintained by a dedicated team. The geographic object data of the ontology library geographic object includes the address of the community, the longitude and latitude coordinates of the community, and other information. The richer the community data in the ontology library community, the higher the accuracy of the evaluation result when the value of the ontology library community is evaluated through the real estate valuation model.

[0044] Non-ontology database geographic objects, also known as housing communities, refer to third-party communities. The geographic object data of non-ontology database geographic objects include the address of the housing community, the longitude and latitude coordinates of the housing community, and other information.

[0045] Sub-cells and parent-cells refer to a cell that may be composed of multiple sub-cells, and the cell is called a parent-cell. For example, a parent-cell "XX City" has multiple sub-cells "XX City Phase I" and "XX City Phase II".

[0046] Mounting means matching the housing community to the entity library community, thereby expanding the information of the entity library community. For example, if the housing community is named "XX" and the entity library community is named "XX Bay", and the two communities are the same community, mounting means associating "XX" and "XX Bay". It should be noted that in order to ensure the uniqueness and matching rate of the entity library community, the matching relationship can be one-to-many, that is, a housing parent community can be associated with multiple entity library child communities.

[0047] Longitude and latitude: Longitude and latitude are coordinates 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°.

[0048] Geospatial index: A data structure designed specifically for storing and querying geospatial data, which plays a key role in processing large amounts of spatial data.

[0049] h3: Divides the Earth's space into recognizable units and encodes longitude and latitude h3 into hexagonal grid indexes.

[0050] Normalization: The process of converting data of different scales or distributions into a common standard range. Its main purpose is to eliminate the dimensional effects between different features. The degree of cell normalization directly affects the quality of cell library data. After the normalization, when users search for relevant information, they can accurately find the target cell and reduce the noise caused by multi-source data.

[0051] The following combination Figure 1-Figure 6The application scenarios of the geographic object processing method provided in the embodiments of the present application are described in detail.

[0052] like Figure 1 As 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. After obtaining the non-ontology library geographic object, it is necessary to clean the multi-source cell data, that is, to standardize the non-ontology library geographic object data. Specifically, the data with the geographic object name prefix and suffix keywords that need to be removed in the non-ontology library geographic object data can be removed according to the pre-set geographic object name prefix and suffix keyword data table; the non-ontology library geographic objects belonging to abnormal types can also be removed according to the pre-set abnormal data type data table. It should be noted that if the non-ontology library geographic objects are removed according to the pre-set geographic object name prefix and suffix keyword data table, if there is a mistaken removal, for example, 100 cells are removed according to the prefix and suffix during the data cleaning process, but there is a cell "XX City Village" in which the "village" meets the prefix and suffix removal keywords, but it is actually found that the cell "XX City Village" is a standard cell, proving that there is a mistaken removal. At this time, other strategies can be used to determine whether the removed cell should be recalled. For abnormal cell longitude and latitude data, the cell's geographic location data can be determined based on the user's geographic location information by determining the geographic location data of the user associated with the cell; or, the cell's geographic location data can be called through a geographic information system to ensure the integrity of the cell's longitude and latitude.

[0053] After classifying abnormal data types through data analysis and cleaning multi-source data according to different cleaning strategies, the multi-source cells are then fused and normalized according to the preset algorithms and fusion strategies. For fusion and normalization of multi-source data, please refer to Figure 2, which is a schematic diagram of the second application scenario of a geographic object processing method provided by the first embodiment of the present application. Specifically, the multi-source cells are quantified into a geographic space grid through a preset uber h3 geographic algorithm. The multi-source cells are multiple housing source cells, which can also be called multiple non-ontology library cells, such as housing source cell A, housing source cell B and housing source cell C. According to the geographic location data of the housing source cell, the geographic space grid corresponding to the housing source cell can be determined. For example, the index of the geographic space grid is grid 1. Then, based on the pre-set grid object mapping table, any ontology library geographic object in grid 1 is obtained, and the grid index where the ontology library geographic object is located is also grid 1. Through the uber h3 geographic algorithm, the non-ontology library geographic object and the ontology library geographic object, which are actually one geographic object, but due to inconsistent geographic location data and inconsistent names of the geographic objects, can be placed in a spatial grid with the ontology library geographic object, and then it is determined whether the non-ontology library geographic object and the ontology library geographic object are one geographic object. For example, the longitude and latitude data of housing community A is 123,456; the longitude and latitude data of community B (the community in the main body library) is 124,466. Through geographic spatial gridding, the geographic spatial index of the two, that is, the h3 index, is the same, that is, housing community A and community B are in the same spatial grid. Then, the fusion strategy described later is used to determine whether they are the same community. If so, the two communities are merged into one community.

[0054] Specifically, when judging whether two communities should be merged together, that is, whether the two communities are the same community, after the two communities fall into one grid, firstly, the distance strategy (obtained through data analysis and mining) is used to determine whether the housing community A and community B are the same community. The parent-child relationship is a separate strategy. The specific process is: use the distance strategy to determine whether the housing community A and community B are the same community. If they are the same community, then make a secondary judgment through the parent-child relationship (data can be returned through the geographic information system interface to build a parent-child relationship data table). If they are parent-child relationships, the two are not the same community. For example, community XX City and community XX City South District are two independent community data. Through the h3 algorithm, the two are in the same grid. Through the distance strategy (such as within 50m), the two are the same community. But in fact, XX City is the parent community and XX City South District is the child community. In the community body library, they should be two independent data. Therefore, the two should not be merged through the parent-child relationship identification.

[0055] In specific implementation, if the distance between the housing source community and the entity database community is within the first preset geographical distance threshold range, for example, 50m, and the two are not in a parent-child relationship, then the two can be determined to be the same community; if the housing source community and the entity database community have the same name, and the distance between the housing source community and the entity database community is within the second preset geographical distance threshold range, for example, 20m, then the two can be determined to be the same community; if the housing source community and the entity database community have similar names, and the distance between the housing source community and the entity database community is within the third preset geographical distance threshold range, for example, 100m, and the two are not in a parent-child relationship, then the two can be determined to be the same community. After the above strategy is used to integrate and normalize the communities, the housing source community and the entity database community can be mounted, and the housing source community data can be used as supplementary data for the entity database community and as a data source for the real estate valuation model.

[0056] It should be noted that after the housing community and the main library community are mounted, the mounting mapping table can be updated. Figure 3 , which is a schematic diagram of the third application scenario of a geographic object processing method provided by the first embodiment of the present application. For example, in the mounting mapping table, if the housing source community matches the entity library community, that is, they are the same community, the housing source community is marked as mounted; if the housing source community does not match the entity library community, that is, they are not the same community, the housing source community is marked as not mounted. For unmounted housing source communities, other methods can be used to judge again. If the housing source community and the entity library community are successfully matched, for communities with abnormal names, the names can be optimized, and the existing data can also be updated and the incremental data can be fused.

[0057] In the process of fusing the housing community data, it is also necessary to process the characteristics of the housing community and the community in the database. Figure 4-Figure 6 The characteristics of the housing community and the community in the ontology library include the floor of the community, the apartment type of the community, the volume ratio of the community, etc. According to the different characteristics of the community, the community type can be divided into foreign-style houses, villas, high-rise buildings, etc. By clustering the community characteristics and building a clustering model, a classification model can also be built. By inputting the characteristics of the community in the community ontology library into the model, the type of the community can be predicted. For example, in community 2, there are both villas and foreign-style houses. It should be noted that the reason for judging the type of community is mainly because different community types have different corresponding community data. By distinguishing the community types, the obtained community data can be made more accurate, thereby improving the quality of community data.

[0058] In the embodiment of the present application, firstly, abnormal data is classified through data analysis and different cleaning strategies are formulated to ensure data accuracy; secondly, the user's geographic location information and the geographic location data of the cell are used by the geographic information system to supplement the longitude and latitude information of the cell, and the cell is allocated to the spatial grid in combination with the uber h3 geographic algorithm, so as to achieve efficient spatial management; finally, the naming differences are eliminated by standardizing the cell name, zoning information and other attributes. Therefore, this solution can improve the consistency of the cell data in the ontology library.

[0059] The above is the full process analysis of the geographic object processing method. The embodiment of the present application provides a geographic object data processing method, including: obtaining a non-ontology library geographic object, the non-ontology library geographic object is a geographic object that does not originate from the ontology library geographic object set; determining the geographic location data of the non-ontology library geographic object; based on the geographic location data of the non-ontology library geographic object, determining the geographic space grid where the non-ontology library geographic object is located as the target geographic space grid; according to a pre-set grid object mapping table, determining any ontology library geographic object in the target geographic space grid as the first target ontology library geographic object, the grid object mapping table records the mapping relationship between the geographic space grid and the ontology library geographic object; according to the geographic location data of the non-ontology library geographic object and the geographic location data of the first target ontology library geographic object, judging whether the non-ontology library geographic object and the first target ontology library geographic object are the same geographic object; if so, using the geographic object data of the non-ontology library geographic object as the supplementary geographic object data of the first target ontology library geographic object.

[0060] The geographic object data processing method described in the embodiment of the present application can determine the geographic space grid where the non-ontology library geographic object is located based on the geographic location data of the non-ontology library geographic object that is not derived from the ontology library geographic object set, and then determine any ontology library geographic object (first target ontology library geographic object) in the geographic space grid where the non-ontology library geographic object is located according to the pre-set grid object mapping table. Finally, based on the geographic location data of the non-ontology library geographic object and the geographic location data of the first target ontology library geographic object, it is determined whether the two are the same geographic object. If so, the geographic object data of the non-ontology library geographic object is used as the supplementary geographic object data of the first target ontology library geographic object, and the geographic object data and the supplementary geographic object data are used together as data for providing geographic object data services to the geographic object data demander. The geographic object data processing method improves the consistency of geographic object data in the ontology library geographic object set.

[0061] The present application is described in detail below through multiple embodiments and drawings.

[0062] First embodiment The first embodiment of the present application provides a method for processing geographic objects. Figure 7 The geographic object data processing method is described in detail.

[0063] Step S701: obtaining a non-ontology library geographical object, wherein the non-ontology library geographical object is a geographical object that does not originate from the ontology library geographical object set.

[0064] This step is used to obtain non-ontology library geographic objects.

[0065] Non-ontology library geographic objects are also called housing source communities, ontology library geographic objects are also called ontology library communities, ontology library geographic object collections are also called ontology library community collections, and community ontology libraries are also called community ontology libraries. The ontology library geographic object collection is a geographic object data source required to provide geographic object data services. For example, the ontology library communities in the ontology library community collection can be used as a data source for a real estate valuation model. The richer the data of the ontology library communities in the ontology library community collection, the higher the accuracy of the evaluation results when the value of the ontology library communities is evaluated through the real estate valuation model.

[0066] In the specific implementation, after obtaining the non-ontology library geographic object, it is also necessary to perform standardization on the non-ontology library geographic object data. Specifically, it can be determined whether there is data matching the prefix and suffix keywords of the geographic object name in the name data of the non-ontology library geographic object according to the pre-set geographic object name prefix and suffix keyword data table; if so, the non-ontology library geographic object is subjected to elimination processing; or, according to the pre-set abnormal data type data table, it is determined whether the type to which the non-ontology library geographic object belongs is an abnormal data type; if so, the non-ontology library geographic object is subjected to elimination processing. If the non-ontology library geographic object is eliminated according to the pre-set geographic object name prefix and suffix keyword data table, if there is an erroneous elimination, for example, 100 communities are eliminated according to the prefix and suffix in the data cleaning process, but one of the communities "XX City Village" has the "village" that meets the keywords eliminated by the prefix and suffix, but it is actually found that the community "XX City Village" is a standard community, proving that there is an erroneous elimination. At this time, other strategies can be used to determine whether the eliminated community should be recalled.

[0067] It should be noted that when identifying abnormal types of non-ontology database geographic objects (communities), first use the data interface of the geographic information system to standardize the types of community data, such as residential and commercial. If the main purpose is to evaluate the value of residential communities, then the commercial category is an abnormal data type and commercial communities need to be removed. When standardizing community data, communities may have a variety of names, such as XX City Phase I, XX City (Gaoyiao Road), XX City, XX City, XX District, XX City, XX Province, etc. The standard name is: XX City, etc., and the names need to be processed uniformly.

[0068] When processing the addresses of residential communities, the addresses in the residential communities and the database generally include the following information: (1) zoning information, such as province, city, county, and township information; (2) road network information, such as road names, road numbers, and road facilities; (3) detailed community information, such as community name, building number, and household number; (4) non-geographic information, such as supplementary instructions, erroneous input, etc. When processing the addresses of residential communities and the database, the original addresses need to be split into independent semantic elements and the types of these elements need to be identified to facilitate the subsequent matching of the residential community addresses and the database community addresses.

[0069] When standardizing the geographic location data of a community, for example, if there are anomalies in the latitude and longitude data of a community, they need to be handled uniformly, and the latitude and longitude data may not be accurate and may be offset, which requires unified handling. For attribute anomalies, such as missing or inaccurate construction years, area, number of buildings, etc. of the community, they need to be handled uniformly. In specific implementation, for abnormalities in the latitude and longitude data of a community, the geographic location data of the community can be determined based on the geographic location information of the user who has an association with the community; or, the geographic location data of the community can be called through the geographic information system to ensure the integrity of the latitude and longitude of the community.

[0070] Step S702: Determine the geographical location data of the non-ontology library geographical object.

[0071] This step is used to determine the geographic location data of non-ontology library geographic objects.

[0072] The geographical location data of the non-ontology library geographical object may specifically be longitude and latitude data, that is, longitude and latitude coordinate data, including longitude data and latitude data.

[0073] Step S703: Based on the geographical location data of the non-ontology library geographical object, determine the geographical space grid where the non-ontology library geographical object is located as the target geographical space grid.

[0074] This step is used to determine the geographic space grid where the non-ontology library geographic object is located based on the geographic location data of the non-ontology library geographic object.

[0075] Step S704: according to a preset grid object mapping table, determine any ontology library geographic object in the target geographic spatial grid as the first target ontology library geographic object, wherein the grid object mapping table records the mapping relationship between the geographic spatial grid and the ontology library geographic object.

[0076] This step is used to determine any ontology library geographic object in the target geospatial grid.

[0077] In the specific implementation, based on the geographical location data of the non-ontology library geographical objects, the geographical space grid where the non-ontology library geographical objects are located is determined, and specifically, the non-ontology library geographical objects are quantified into the geographical space grid through the preset uber h3 geographical algorithm. The uber h3 geographical algorithm can divide the earth space into hexagonal ranges, and each hexagon uniquely corresponds to an h3 index. By gridding the entire space, each geographical object can fall into a spatial grid through the geographical location data. Through the uber h3 geographical algorithm, the non-ontology library geographical objects and the ontology library geographical objects that are actually the same geographical object, but due to inconsistent geographical location data and inconsistent names of the geographical objects, the non-ontology library geographical objects and the ontology library geographical objects can be placed in the same spatial grid, and then it is determined whether the non-ontology library geographical objects and the ontology library geographical objects are the same geographical object. For example, the longitude and latitude data of housing community A is 123,456; the longitude and latitude data of community B (the community in the ontology library) is 124,466. Through geographic space gridding, the h3 indexes of the two are the same, that is, housing community A and community B are in the same spatial grid. Then, the fusion strategy described later is used to determine whether they are the same community. If so, the two communities are merged into one community.

[0078] In an embodiment of the present application, determining any one ontology library geographic object in the target geographic spatial grid as the first target ontology library geographic object according to a pre-set grid object mapping table includes: based on the geographic location data of the non-ontology library geographic object, determining any one ontology library geographic object in the target geographic spatial grid whose geographic distance with the geographic location of the non-ontology library geographic object is within a preset geographic distance threshold range as the first target ontology library geographic object.

[0079] Step S705: judging whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object according to the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object.

[0080] This step is used to determine whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object based on the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object.

[0081] As an embodiment, judging whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object based on the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object includes: determining the geographical location matching degree between the non-ontology library geographical object and the first target ontology library geographical object based on the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object; judging whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object based on the geographical location matching degree.

[0082] The method of determining the geographic location matching degree between the non-ontology library geographic object and the first target ontology library geographic object includes: determining the geographic distance data between the non-ontology library geographic object and the first target ontology library geographic object based on the geographic location data of the non-ontology library geographic object and the geographic location data of the first target ontology library geographic object; judging whether the geographic distance data is less than a first geographic distance data threshold value to obtain a first judgment result; and determining the geographic location matching degree between the non-ontology library geographic object and the first target ontology library geographic object based on the first judgment result. In a specific implementation, the matching degree in the geographic location matching degree can be represented by a 0-1 interval value. In a specific implementation, different matching results between the non-ontology library geographic object and the first target ontology library geographic object can be pre-set to correspond to different value intervals. The higher the matching degree between the non-ontology library geographic object and the first target ontology library geographic object, the higher the corresponding value interval. If it is a complete match, the value can be 1.

[0083] It should be noted that, based on the above steps, it has been determined that the non-ontology library geographical object and the first target ontology library geographical object are in the same geographic space grid. At this time, it is necessary to further determine whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object. Specifically, the determination is made based on the geographical location matching degree between the non-ontology library geographical object and the first target ontology library geographical object. When determining the geographical location matching degree between the non-ontology library geographical object and the first target ontology library geographical object, it is specifically determined based on the geographical distance data between the non-ontology library geographical object and the first target ontology library geographical object, that is, whether the geographical distance data is less than the first geographical distance data threshold, for example, 50m, to obtain a first judgment result. According to the first judgment result, the geographical location matching degree between the non-ontology library geographical object and the first target ontology library geographical object is determined.

[0084] Assume that the latitude and longitude of the non-ontology library geographic object is ; The longitude and latitude of the geographic object in the first target ontology library is . The geographic distance data between the geographical objects in the non-ontology library and the geographical objects in the first target ontology library can be calculated using geographic information system (GIS) technology, where the calculation of the geographical distance can be approximated based on the spherical model, that is, the earth is regarded as a standard ellipsoid and the curve distance between two points on the sphere is calculated. In specific implementation, GeoDistanceSortBuilder can be used for sorting, that is, geo_dis sorting. When using geo_dis sorting, you first need to define an index and create a field with a data type of geo_point in the index to store 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 according to the distance. Calculate the geographic distance data between the geographical objects in the non-ontology library and the geographical objects in the first target ontology library, and set a certain distance threshold , ensure that the geographical distance data between the non-ontology library geographical object and the first target ontology library geographical object is within the distance range, that is .

[0085] In specific implementation, it is also necessary to determine whether the non-ontology library geographical object and the first target ontology library geographical object are parent-child geographical objects to obtain a second judgment result; the determination of whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object based on the geographical location matching degree includes: determining whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object based on the geographical location matching degree and the second judgment result. The determination of whether the non-ontology library geographical object and the first target ontology library geographical object are parent-child geographical objects to obtain a second judgment result includes: determining a child geographical object of the first target ontology library geographical object as an 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; determining whether the non-ontology library geographical object and the first target ontology library geographical object 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 second judgment result.

[0086] The determining, based on the geographic location matching degree and the second judgment result, whether the non-ontology library geographic object and the first target ontology library geographic object are the same geographic object comprises: if the geographic location matching degree is higher than a geographic location matching degree threshold, and the non-ontology library geographic object and the first target ontology library geographic object are not parent-child geographic objects, determining that the non-ontology library geographic object and the first target ontology library geographic object are the same geographic object.

[0087] In the specific implementation, it is also necessary to limit the parent-child relationship between the housing source community and the ontology database community to avoid the ontology database community being the parent community of the housing source community. Assume that the name data of the ontology database child 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 library sub-community need to meet the following conditions: .

[0088] In the above embodiment, the fusion strategy of the housing source community and the entity database community is distance and parent-child relationship judgment. If the distance between the housing source community and the entity database community is relatively close, such as 50m, and the two are not in a parent-child relationship, it can be determined that the two are the same community.

[0089] As an embodiment, when determining whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object, the address text data of the non-ontology library geographical object and the address text data of the first target ontology library geographical object can also be determined; the address text matching degree between the non-ontology library geographical object and the first target ontology library geographical object is determined based on the address text data of the non-ontology library geographical object and the address text data of the first target ontology library geographical object; judging whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object based on the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object includes: judging whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object based on the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object and the address text matching degree between the non-ontology library geographical object and the first target ontology library geographical object.

[0090] The determining of the address text matching degree between the non-ontology library geographical object and the first target ontology library geographical object based on the address text data of the non-ontology library geographical object and the address text data of the first target ontology library geographical object comprises: judging whether the geographical object name data of the non-ontology library geographical object is the same as the geographical object name data of the first target ontology library geographical object to obtain a third judgment result; and determining the address text matching degree between the non-ontology library geographical object and the first target ontology library geographical object based on the third judgment result.

[0091] During specific implementation, it can also be determined whether the geographical object name data of the non-ontology library geographical object is the same as the geographical object name data of the first target ontology library geographical object. If the geographical object name data of the non-ontology library geographical object is the same as the geographical object name data of the first target ontology library geographical object, and the geographical distance data between the non-ontology library geographical object and the first target ontology library geographical object is also within the preset geographical distance range, it is determined that the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object.

[0092] The determining, based on the geographic location matching degree, whether the non-ontology library geographic object and the first target ontology library geographic object are the same geographic object comprises: determining the geographic distance data between the non-ontology library geographic object and the first target ontology library geographic object based on the geographic location data of the non-ontology library geographic object and the geographic location data of the first target ontology library geographic object; and determining whether the geographic distance data is less than a second geographic distance data threshold value. , obtain a fourth judgment result; according to the fourth judgment result, determine the geographical location matching degree between the non-ontology library geographical object and the first target ontology library geographical object, that is, the distance restriction satisfies .

[0093] The determining whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object based on the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object and the address text matching degree between the non-ontology library geographical object and the first target ontology library geographical object comprises: if the address text matching degree is higher than the address text matching degree threshold, and the geographical location matching degree is higher than the geographical location matching degree threshold, determining that the non-ontology library geographical object and any one of the ontology library geographical objects are the same geographical object.

[0094] In the above embodiment, the fusion strategy of the housing source community and the ontology library community is the same distance and name. If the name of the housing source community and the ontology library community is the same, and the distance range is within the preset distance threshold range, such as 200m, then it can be determined that the two are the same community. It should be noted that in the above embodiment, the geographical distance threshold is relatively small, such as 50m. If the geographical object name data of the non-ontology library geographical object is the same as the geographical object name data of the first target ontology library geographical object, then the threshold of the geographical distance restriction is It is relatively high, for example, 200m, because two geographic objects with the same name can basically determine that the two geographic objects are the same geographic object, so the distance limit is wider.

[0095] As an embodiment, determining the address text matching degree between the non-ontology library geographical object and the first target ontology library geographical object based on the address text data of the non-ontology library geographical object and the address text data of the first target ontology library geographical object includes: determining the name matching degree between the non-ontology library geographical object and the first target ontology library geographical object based on the geographical object name data of the non-ontology library geographical object and the geographical object name data of the first target ontology library geographical object.

[0096] The method of determining the name matching degree between the non-ontology library geographical object and the first target ontology library geographical object according to the geographical object name data of the non-ontology library geographical object and the geographical object name data of the first target ontology library geographical object comprises: 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 the first target ontology library geographical object; determining the string length value of the geographical object name data of the non-ontology library geographical object and the geographical object name data of the first target ontology library geographical object, whichever has the larger string length value, as the target string length value according to the string length value of the geographical object name data of the non-ontology library geographical object and the string length value of the geographical object name data of the first target ontology library geographical object; traversing all characters in the string of the geographical object name data of the non-ontology library geographical object and the geographical object name data of the first target ontology library geographical object; determining the first substring between the first character in the string corresponding to the geographical object name data of the non-ontology library geographical object and the previous character of the currently traversed character and the first substring between the first character in the string corresponding to the geographical object name data of the first target ontology library geographical object and the previous character of the currently traversed character. a second substring between the characters traversed; based on the first substring and the second substring, determining 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 the first target ontology library geographical object; determining a 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 character currently traversed and a fourth substring between the first character in the string corresponding to the geographical object name data of the first target ontology library geographical object and the character before the character currently traversed; based on the third substring and the fourth substring, determining 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 the first target ontology library geographical object; 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 character string length value is greater than a preset ratio threshold value, and obtaining an eighth judgment result; and determining the name matching degree between the non-ontology library geographical object and the first target ontology library geographical object according to the eighth judgment result.

[0097] When matching the names of non-ontology database geographic objects with the first target ontology database geographic objects, the longest common subsequence sorting algorithm is used to sort the names of the housing source communities and ontology database communities 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 subsequence shared by two sequences. In specific implementation, LCS needs to meet the following conditions:

[0098] "max(a,b)" means taking the larger number between 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 the characters in the string are traversed.

[0099] It should be noted that when calculating the longest common subsequence length value of the geographic object name data of a non-ontology library geographic object and any ontology library geographic object in the ontology library geographic object set, a data table for recording the longest common subsequence length value between character pairs consisting of characters in a string corresponding to the geographic object name data of the non-ontology library geographic object and characters in a string corresponding to the geographic object name data of any ontology library geographic object can be first established. Then, each character in the string corresponding to the geographic object name data of the non-ontology library geographic object is compared one by one with all characters in the string corresponding to the geographic object name data of any ontology library geographic object. When two characters match, the longest common subsequence length can be updated according to 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 library string and the ontology library string can be obtained.

[0100] When determining the name matching degree between the non-ontology library geographical object and the first target ontology library geographical object, it can also be judged according to the vector. Specifically, the name matching degree between the non-ontology library geographical object and the first target ontology library geographical object is determined according to the geographical object name data of the non-ontology library geographical object and the geographical object name data of the first target ontology library geographical object, including: determining a first vector of the geographical object name data of the non-ontology library geographical object; determining a second vector of the geographical object name data of the first target ontology library geographical object; judging whether the similarity between the first vector and the second vector is greater than a preset vector similarity threshold, and obtaining a fifth judgment result; and determining the name matching degree between the non-ontology library geographical object and the first target ontology library geographical object according to the fifth judgment result.

[0101] When determining whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object, when the name similarity between the non-ontology library geographical object and the first target ontology library geographical object meets the preset conditions, it is also necessary to determine whether the geographical distance data between the non-ontology library geographical object and the first target ontology library geographical object meets the preset geographical distance threshold. Specifically, the determination of the geographical location matching degree between the non-ontology library geographical object and the first target ontology library geographical object includes: determining the geographical distance data between the non-ontology library geographical object and the first target ontology library geographical object based on the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object; and determining whether the geographical distance data is less than a third geographical distance data threshold , for example, 100m, to obtain a sixth judgment result; according to the sixth judgment result, determine the geographical location matching degree between the non-ontology library geographical object and the first target ontology library geographical object, that is, .

[0102] In specific implementation, it is also necessary to determine whether the non-ontology library geographical object and the first target ontology library geographical object are parent-child geographical objects to obtain a seventh judgment result; the determination of whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object based on the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object and the address text matching degree between the non-ontology library geographical object and the first target ontology library geographical object, includes: determining whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object based on the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object, the address text matching degree between the non-ontology library geographical object and the first target ontology library geographical object and the seventh judgment result.

[0103] The determining whether the non-ontology library geographical object and the first target ontology library geographical object are parent-child geographical objects to obtain a seventh determination result includes: determining a child geographical object of the first target ontology library geographical object as an ontology library child geographical object; determining geographical object name data of the ontology library child geographical object; determining a 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; determining whether the non-ontology library geographical object and the first target ontology library geographical object 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 to obtain the seventh determination result.

[0104] The determining whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object based on the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object, the address text matching degree between the non-ontology library geographical object and the first target ontology library geographical object, and the seventh judgment result includes: if the address text matching degree is higher than the address text matching degree threshold, the geographical location matching degree is higher than the geographical location matching degree threshold, and the non-ontology library geographical object and the first target ontology library geographical object are not parent-child geographical objects, then determining that the non-ontology library geographical object and any one of the ontology library geographical objects are the same geographical object.

[0105] In the specific implementation, it is also necessary to limit the parent-child relationship between the housing source community and the ontology database community to avoid the ontology database community being the parent community of the housing source community. Assume that the name data of the ontology database child 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 library sub-community need to meet the following conditions: .

[0106] In the above embodiment, the fusion strategy of the housing source community and the main library community is name, distance and parent-child relationship judgment. If the distance between the housing source community and the main library community is within the preset distance threshold range, such as 100m, and the two are not in a parent-child relationship, it can be determined that the two are the same community.

[0107] Step S706: If yes, the geographical object data of the non-ontology library geographical object is used as the supplementary geographical object data of the first target ontology library geographical object.

[0108] This step is used to use the geographical object data of the non-ontology library geographical object as the supplementary geographical object data of the first target ontology library geographical object when the non-ontology library geographical object and any one of the ontology library geographical objects are the same geographical object. The geographical object data and the supplementary geographical object data are used together as data for providing geographical object data services to the geographical object data demander, thereby enriching the geographical object data of the ontology library geographical object.

[0109] In a specific implementation, if the non-ontology library geographical object is the same geographical object as any one of the ontology library geographical objects, the non-ontology library geographical object can be associated with the first target ontology library geographical object in the mounting data table, and the mounting data table can also be called a mapping relationship table, and the mounting data table is a data table for recording the mapping relationship between the ontology library geographical object and the non-ontology library geographical object. The mounting data table described in the embodiment of the present application also includes: a judgment method for judging whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object. For example, the judgment methods mentioned above include: the distance between the non-ontology library geographical object and the first target ontology library geographical object is within the first preset geographical distance data threshold range, such as 50m, and there is no parent-child relationship between the non-ontology library geographical object and the first target ontology library geographical object; the non-ontology library geographical object and the first target ontology library geographical object have the same name, and the distance between the non-ontology library geographical object and the first target ontology library geographical object is within the second preset geographical distance data threshold range, such as 200m; the non-ontology library geographical object and the first target ontology library geographical object have similar names, and the distance between the non-ontology library geographical object and the first target ontology library geographical object is within the third preset geographical distance data threshold range, such as 100m, and there is no parent-child relationship between the non-ontology library geographical object and the first target ontology library geographical object.

[0110] In an embodiment of the present application, the geographic object data of the non-ontology library geographic object is used as the supplementary geographic object data of the first target ontology library geographic object, including: obtaining the first target ontology library geographic object as the geographic object to be evaluated; obtaining the target ontology library geographic object data and the supplementary geographic object data of the geographic object to be evaluated from the geographic object database used to store geographic object data; obtaining the geographic object data required for evaluating the resource data of the geographic object to be evaluated from the target 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 the 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 of the ontology library community set, the higher the accuracy of the evaluation result when the value of the ontology library community is evaluated through the real estate valuation model.

[0111] The embodiment of the present application provides the geographic object data processing method, which can effectively remove inaccurate or erroneous information by cleaning and filtering abnormal data and using different strategies to clean the data, thereby improving the quality of the overall data set and facilitating subsequent data analysis; using the user's geographic location information and using the geographic information system to call the geographic location data of the cell to supplement the longitude and latitude information of the cell, ensuring that each cell record has complete location information; using the uber h3 geographic algorithm to allocate the cell to a specific spatial grid, it is helpful to better understand and manage the urban spatial distribution, which not only improves the data organization efficiency, but also lays the foundation for subsequent spatial analysis; by implementing standardized processing on the main name of the cell, zoning information and other attributes, it can eliminate confusion caused by naming differences and the like, which is conducive to data comparison between different regions; by formulating multiple sets of fusion strategies, the application of data processing is made more flexible and extensive.

[0112] The embodiment of the present application provides a method for processing geographic object data, including: obtaining a non-ontology library geographic object, wherein the non-ontology library geographic object is a geographic object that does not originate from an ontology library geographic object set; determining geographic location data of the non-ontology library geographic object; based on the geographic location data of the non-ontology library geographic object, determining a geographic space grid where the non-ontology library geographic object is located as a target geographic space grid; according to a pre-set grid object mapping table, determining any one ontology library geographic object in the target geographic space grid as a first target ontology library geographic object, wherein the grid object mapping table records a mapping relationship between a geographic space grid and an ontology library geographic object; according to the geographic location data of the non-ontology library geographic object and the geographic location data of the first target ontology library geographic object, determining whether the non-ontology library geographic object and the first target ontology library geographic object are the same geographic object; if so, using the geographic object data of the non-ontology library geographic object as the supplementary geographic object data of the first target ontology library geographic object.

[0113] The geographic object data processing method described in the embodiment of the present application can determine the geographic space grid where the non-ontology library geographic object is located based on the geographic location data of the non-ontology library geographic object that is not derived from the ontology library geographic object set, and then determine any ontology library geographic object (first target ontology library geographic object) in the geographic space grid where the non-ontology library geographic object is located according to the pre-set grid object mapping table. Finally, based on the geographic location data of the non-ontology library geographic object and the geographic location data of the first target ontology library geographic object, it is determined whether the two are the same geographic object. If so, the geographic object data of the non-ontology library geographic object is used as the supplementary geographic object data of the first target ontology library geographic object, and the geographic object data and the supplementary geographic object data are used together as data for providing geographic object data services to the geographic object data demander. The geographic object data processing method improves the consistency of geographic object data in the ontology library geographic object set.

[0114] Second embodiment In the above first embodiment, 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 basically similar to the first method embodiment, the description is relatively simple. For relevant parts, please refer to the partial description of the method embodiment. The device embodiment described below is only illustrative.

[0115] Please refer to Figure 8 , which is a schematic diagram of a geographic object processing device provided in the second embodiment of the present application.

[0116] The geographic object processing device 800 comprises: The non-ontology library geographical object obtaining unit 801 is used to obtain the non-ontology library geographical object, wherein the non-ontology library geographical object is a geographical object that does not originate from the ontology library geographical object set; A geographical location data determining unit 802 is used to determine the geographical location data of the non-ontology library geographical object; A target geospatial grid determining unit 803 is used to determine the geospatial grid where the non-ontology library geographic object is located based on the geographic location data of the non-ontology library geographic object as the target geospatial grid; A first target ontology library geographic object determination unit 804 is used to determine any ontology library geographic object in the target geographic spatial grid as the first target ontology library geographic object according to a preset grid object mapping table, wherein the grid object mapping table records the mapping relationship between the geographic spatial grid and the ontology library geographic object; A judging unit 805 is used to judge whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object according to the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object; The supplementary geographic object data obtaining unit 806 is configured to use the geographic object data of the non-ontology library geographic object as the supplementary geographic object data of the first target ontology library geographic object.

[0117] Third embodiment Corresponding to the above method embodiment of the present application, the third embodiment of the present application further provides an electronic device. Fig. 9 As shown, Fig. 9 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 901, at least one communication interface 902, at least one memory 903 and at least one communication bus 904; optionally, the communication interface 902 may be an interface of a communication module, such as an interface of a GSM module; the processor 901 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 an embodiment of the present invention. The memory 903 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. Among them, the memory 903 stores a program, and the processor 901 calls the program stored in the memory 903 to execute the method provided in the above embodiment of the present application.

[0118] Fourth embodiment 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.

[0119] Although the present application is disclosed as above in the form of a preferred embodiment, it is not intended to limit the present application. Any technical personnel in this field 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.

[0120] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0121] 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.

[0122] 1. Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be used to store information by any method or technology. 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 memory (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 technology, 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 media such as modulated data signals and carrier waves.

[0123] 2. Those skilled in the art should understand that the embodiments of the present application can be provided as methods, systems or computer program products. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0124] It should be noted that the embodiments of the present 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.).

[0125] 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 data processing method, characterized in that: include: Obtaining a non-ontology library geographic object, wherein the non-ontology library geographic object is a geographic object that does not originate from the ontology library geographic object set; Determine the geographic location data of the non-ontology library geographic object; Based on the geographical location data of the non-ontology library geographical object, determining the geographical space grid where the non-ontology library geographical object is located as the target geographical space grid; According to a preset grid object mapping table, determining any ontology library geographic object in the target geographic spatial grid as a first target ontology library geographic object, wherein the grid object mapping table records a mapping relationship between the geographic spatial grid and the ontology library geographic object; According to the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object, determining whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object; If yes, the geographic object data of the non-ontology library geographic object is used as the supplementary geographic object data of the first target ontology library geographic object.

2. The geographic object data processing method according to claim 1, characterized in that: The determining, based on the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object, whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object comprises: Determining a geographic location match between the non-ontology library geographic object and the first target ontology library geographic object according to the geographic location data of the non-ontology library geographic object and the geographic location data of the first target ontology library geographic object; According to the geographical location matching degree, it is determined whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object.

3. The geographic object data processing method according to claim 2, characterized in that: The determining of the geographical location matching degree between the non-ontology library geographical object and the first target ontology library geographical object includes: Determine the geographical distance data between the non-ontology library geographical object and the first target ontology library geographical object according to the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object; Determine whether the geographic distance data is less than a first geographic distance data threshold, and obtain a first determination result; According to the first judgment result, the geographical location matching degree between the non-ontology library geographical object and the first target ontology library geographical object is determined.

4. The geographic object data processing method according to claim 3, characterized in that: Also includes: Determine whether the non-ontology library geographical object and the first target ontology library geographical object are parent-child geographical objects to obtain a second determination result; The step of judging whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object according to the geographical location matching degree includes: According to the geographical location matching degree and the second judgment result, it is determined whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object.

5. The geographic object data processing method according to claim 4, characterized in that: The determining whether the non-ontology library geographical object and the first target ontology library geographical object are parent-child geographical objects to obtain a second determination result includes: Determine a sub-geographical object of the first target 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 the 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 the first target ontology library geographic object are parent-child geographic objects to obtain the second determination result.

6. The geographic object data processing method according to claim 4, characterized in that: The step of judging, based on the geographical location matching degree and the second judgment result, whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object includes: If the geographic location matching degree is higher than the geographic location matching degree threshold, and the non-ontology library geographic object and the first target ontology library geographic object are not parent-child geographic objects, it is determined that the non-ontology library geographic object and the first target ontology library geographic object are the same geographic object.

7. The geographic object data processing method according to claim 2, characterized in that: Also includes: Determine the address text data of the non-ontology library geographic object and the address text data of the first target ontology library geographic object; Determining the address text matching degree between the non-ontology library geographical object and the first target ontology library geographical object according to the address text data of the non-ontology library geographical object and the address text data of the first target ontology library geographical object; The determining, based on the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object, whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object comprises: According to the geographic location data of the non-ontology library geographic object and the geographic location data of the first target ontology library geographic object and the address text matching degree between the non-ontology library geographic object and the first target ontology library geographic object, it is determined whether the non-ontology library geographic object and the first target ontology library geographic object are the same geographic object.

8. The geographic object data processing method according to claim 7, characterized in that: The determining, based on the address text data of the non-ontology library geographic object and the address text data of the first target ontology library geographic object, the address text matching degree between the non-ontology library geographic object and the first target 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 the first target ontology library geographical object, and obtain a third determination result; According to the third judgment result, the address text matching degree between the non-ontology library geographical object and the first target ontology library geographical object is determined.

9. The geographic object data processing method according to claim 7, characterized in that: The step of judging whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object according to the geographical location matching degree includes: Determine the geographical distance data between the non-ontology library geographical object and the first target ontology library geographical object according to the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object; Determine whether the geographic distance data is less than a second geographic distance data threshold to obtain a fourth determination result; According to the fourth judgment result, the geographical location matching degree between the non-ontology library geographical object and the first target ontology library geographical object is determined.

10. The geographic object data processing method according to claim 7, characterized in that: The determining, based on the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object and the address text matching degree between the non-ontology library geographical object and the first target ontology library geographical object, whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object comprises: 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 first target ontology library geographic object are the same geographic object.

11. The geographic object data processing method according to claim 7, characterized in that: The determining, based on the address text data of the non-ontology library geographic object and the address text data of the first target ontology library geographic object, the address text matching degree between the non-ontology library geographic object and the first target ontology library geographic object comprises: The name matching degree between the non-ontology library geographical object and the first target ontology library geographical object is determined according to the geographical object name data of the non-ontology library geographical object and the geographical object name data of the first target ontology library geographical object.

12. The geographic object data processing method according to claim 11, characterized in that: The determining, based on the geographical object name data of the non-ontology library geographical object and the geographical object name data of the first target ontology library geographical object, the name matching degree between the non-ontology library geographical object and the first target ontology library geographical object comprises: Determine a first vector of geographic object name data of the non-ontology library geographic object; Determine a second vector of geographic object name data of the geographic object in the first target ontology library; Determine whether the similarity between the first vector and the second vector is greater than a preset vector similarity threshold, to obtain a fifth determination result; According to the fifth judgment result, the name matching degree between the non-ontology library geographical object and the first target ontology library geographical object is determined.

13. The geographic object data processing method according to claim 11, characterized in that: The determining of the geographical location matching degree between the non-ontology library geographical object and the first target ontology library geographical object includes: Determine the geographical distance data between the non-ontology library geographical object and the first target ontology library geographical object according to the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object; Determine whether the geographic distance data is less than a third geographic distance data threshold to obtain a sixth determination result; According to the sixth judgment result, the geographical location matching degree between the non-ontology library geographical object and the first target ontology library geographical object is determined.

14. The geographic object data processing method according to claim 11, characterized in that: Also includes: Determine whether the non-ontology library geographical object and the first target ontology library geographical object are parent-child geographical objects to obtain a seventh determination result; The determining, based on the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object and the address text matching degree between the non-ontology library geographical object and the first target ontology library geographical object, whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object comprises: Based on the geographic location data of the non-ontology library geographic object and the geographic location data of the first target ontology library geographic object, the address text matching degree between the non-ontology library geographic object and the first target ontology library geographic object, and the seventh judgment result, it is determined whether the non-ontology library geographic object and the first target ontology library geographic object are the same geographic object.

15. The geographic object data processing method according to claim 14, characterized in that: The determining whether the non-ontology library geographical object and the first target ontology library geographical object are parent-child geographical objects to obtain a seventh determination result includes: Determine a sub-geographical object of the first target 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 the 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 the first target ontology library geographic object are parent-child geographic objects to obtain the seventh determination result.

16. The geographic object data processing method according to claim 14, characterized in that: The step of judging whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object according to the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object, the address text matching degree between the non-ontology library geographical object and the first target ontology library geographical object, and the seventh 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 the target ontology library geographic object are not parent-child geographic objects, then it is determined that the non-ontology library geographic object and the first target ontology library geographic object are the same geographic object.

17. The geographic object data processing method according to claim 1, characterized in that: Also includes: If the non-ontology library geographical object and the first target ontology library geographical object are not the same geographical object, then determining any ontology library geographical object in the target geographic spatial grid except the first target ontology library geographical object as the second target ontology library geographical object; According to the geographical location data of the non-ontology library geographical object and the geographical location data of the second target ontology library geographical object, determining whether the non-ontology library geographical object and the second target ontology library geographical object are the same geographical object; If not, traverse any other ontology library geographic object in the target geographic spatial grid except the first target ontology library geographic object and the second target ontology library geographic object again until the non-ontology library geographic object is the same as any other ontology library geographic object.

18. The geographic object data processing method according to claim 1, characterized in that: After obtaining the non-ontology library geographic object, the method further includes: According to a preset geographical object name prefix and suffix keyword data table, determining whether there is data matching the geographical object name prefix and suffix keywords in the name data of the non-ontology library geographical object; If yes, then a removal process is performed on the non-ontology library geographic objects; Alternatively, according to a preset abnormal data type data table, determining whether the type to which the non-ontology library geographic object belongs is an abnormal data type; If so, a removal process is performed on the non-ontology library geographic objects.

19. The geographic object data processing method according to claim 1, characterized in that: The step of using the geographical object data of the non-ontology library geographical object as the supplementary geographical object data of the first target ontology library geographical object includes: Obtaining a first target ontology library geographic object as the geographic object to be evaluated; Obtaining the target ontology library geographic object data and supplementary geographic object data of the geographic object to be evaluated from a geographic object database for storing geographic object data; Obtaining geographic object data required for evaluating resource data of the geographic object to be evaluated from the target ontology library geographic object data and the supplementary geographic object data of the geographic object to be evaluated; The resource data of the to-be-evaluated geographical object is evaluated according to the required geographical object data.

20. A geographic object data processing device, characterized in that: include: A non-ontology library geographical object obtaining unit, used to obtain a non-ontology library geographical object, wherein the non-ontology library geographical object is a geographical object that does not originate from the ontology library geographical object set; A geographical location data determining unit, used to determine the geographical location data of the non-ontology library geographical object; A target geospatial grid determination unit, configured to determine, based on the geographical location data of the non-ontology library geographical object, the geospatial grid where the non-ontology library geographical object is located as the target geospatial grid; A first target ontology library geographic object determination unit, configured to determine any ontology library geographic object in the target geographic spatial grid as the first target ontology library geographic object according to a preset grid object mapping table, wherein the grid object mapping table records a mapping relationship between the geographic spatial grid and the ontology library geographic object; A judging unit, configured to judge whether the non-ontology library geographical object and the first target ontology library geographical object are the same geographical object according to the geographical location data of the non-ontology library geographical object and the geographical location data of the first target ontology library geographical object; The supplementary geographic object data obtaining unit is configured to use the geographic object data of the non-ontology library geographic object as the supplementary geographic object data of the first target ontology library geographic object.

21. An electronic device, characterized in that: The electronic device comprises a processor and a memory; The memory stores a computer program, and after the processor runs the computer program, the method according to any one of claims 1 to 19 is executed.

22. 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 19 is executed.

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