Address information improvement method, system and device and storage medium

Abstract

The invention discloses an address information improvement method, system and device and a storage medium. In the scheme, target address information is acquired; and judging the information type of the target address information based on the information content contained in the target address information, and performing information supplementation processing on the target address information through the information type to obtain first address information. And calling a third-party API interface based on the first address information to obtain second address information and latitude and longitude coordinates. The first address information, the second address information and the latitude and longitude coordinates are integrated, redundant information is removed, the improved target address information is obtained, the efficiency and accuracy of address information improvement are remarkably improved, and the overall quality of the address information is improved.

Description

Technical Field

[0001] This application relates to the technical field of data processing, and particularly to a method, apparatus, device, and storage medium for improving address information. Background Art

[0002] With the rapid development and wide application of information technology, information processing plays a crucial role in all walks of life. Whether it is enterprise operation, government services, or personal daily life, it is inseparable from accurate and efficient information processing support. Especially in customer information management, address information, as one of the key data, its accuracy and integrity are directly related to the subsequent service provision, contract execution, and effective risk management.

[0003] However, in the current information processing process, the address information filled in by customers generally has problems such as being chaotic, redundant, and missing. These problems not only lead to inaccurate address information but also seriously affect the efficiency and accuracy of information processing.

[0004] Traditional methods for improving address information often rely on manual review and correction. This method is not only time-consuming and laborious but also difficult to meet the needs of large-scale data processing. In addition, due to the subjectivity and differences of manual review, the consistency and accuracy of address information are also difficult to be fully guaranteed. Summary of the Invention

[0005] Based on the above problems, this application provides a method, system, device, and storage medium for improving address information, aiming to improve the efficiency and accuracy of address information improvement, thereby enhancing the overall quality of address information.

[0006] The embodiments of this application disclose the following technical solutions:

[0007] In a first aspect of this application, a method for improving address information is provided. The method includes:

[0008] Obtain target address information;

[0009] Judge the information type of the target address information based on the information content included in the target address information;

[0010] Perform information supplementation processing on the target address information based on the information type to obtain first address information;

[0011] Call a third-party API interface based on the first address information to obtain second address information and longitude and latitude coordinates;

[0012] Integrate the first address information, the second address information, and the longitude and latitude coordinates, and remove redundant information to obtain the improved target address information.

[0013] In an alternative implementation, calling a third-party API interface based on the first address information to obtain second address information and longitude and latitude coordinates includes:

[0014] Removing the maximum repeated strings from the first address information to obtain the de-duplicated first address information;

[0015] Calling a third-party API interface based on the de-duplicated first address information to obtain second address information and longitude and latitude coordinates.

[0016] In an alternative implementation, the information type includes a first type, a second type, and a third type; determining the information type of the target address information based on the information content included in the target address information includes:

[0017] When the target address information includes both address name information and province / city / county (district) code information, determining that the information type of the target address information is the first type;

[0018] When the target address information includes address name information but does not include province / city / county (district) code information, and the address name information includes province / city / county (district) name information, determining that the information type of the target address information is the second type;

[0019] When the target address information includes address name information but does not include province / city / county (district) code information, and the address name information does not include one or more of the province / city / county (district) name information, determining that the information type of the target address information is the third type.

[0020] In an alternative implementation, the target address information includes postal code information; performing information supplementation processing on the target address information based on the information type to obtain first address information includes:

[0021] When the information type is the first type, obtaining province / city / county (district) name information based on the province / city / county (district) code information, and supplementing the province / city / county (district) name information to the target address information to obtain first address information;

[0022] When the information type is the second type, parsing and obtaining province / city / county (district) name information based on the address name information using a pre-trained language representation model, obtaining province / city / county (district) code information based on the province / city / county (district) name information, and supplementing the province / city / county (district) name information and the province / city / county (district) code information to the target address information to obtain first address information;

[0023] When the information type is the third type, based on the postal code information in the address information, use the pre-constructed postal code table to determine the name information of the province, city, county (district) corresponding to the address name information, and obtain the province, city, county (district) code information based on the name information of the province, city, county (district). Supplement the name information of the province, city, county (district) and the province, city, county (district) code information into the target address information to obtain the first address information.

[0024] In an alternative implementation, the construction method of the pre-constructed postal code table includes:

[0025] Obtain the mapping relationship between the street postal code and the province, city, county (district);

[0026] According to the mapping relationship, construct a postal code table including the street postal code and the corresponding province, city, county (district) information.

[0027] In an alternative implementation, the training method of the language representation model includes:

[0028] Obtain training samples; the training samples include address information text data and their corresponding annotation labels;

[0029] Preprocess the training samples, and divide the preprocessed training samples into a training set, a validation set and a test set;

[0030] Use a pre-encoder to convert the original text data into an input data format acceptable to the language representation model;

[0031] Optimize the parameters of the language representation model based on the converted training set;

[0032] Evaluate the language representation model with optimized parameters based on the model performance evaluation index, and further adjust and optimize the parameters of the language representation model according to the evaluation results.

[0033] In an alternative implementation, the address information improvement method further includes:

[0034] Based on the spatial indexing algorithm, convert the longitude and latitude coordinates into a comparable string code;

[0035] Grid the improved target address information based on the string code.

[0036] The second aspect of the present application provides an address information improvement system, which includes:

[0037] An address acquisition module, configured to acquire target address information; the target address information is the address information to be improved;

[0038] A type judgment module, configured to judge the information type of the target address information based on the information content included in the target address information;

[0039] An address supplement module, configured to perform information supplement processing on the target address information based on the information type to obtain first address information;

[0040] An API call module, configured to call a third-party API interface based on the first address information to obtain second address information and longitude and latitude coordinates;

[0041] An address improvement module, configured to integrate the first address information, the second address information, and the longitude and latitude coordinates, and remove redundant information to obtain the improved target address information.

[0042] A third aspect of the present application provides an address information improvement device, which includes: a processor and a memory:

[0043] The memory is used to store program code and transmit the program code to the processor;

[0044] The processor is configured to execute the steps of the address information improvement method described in any implementation manner of the first aspect according to the instructions in the program code.

[0045] A fourth aspect of the present application provides a computer-readable storage medium, which is used to store program code, and the program code is used to execute the steps of the address information improvement method described in any implementation manner of the first aspect. Compared with the prior art, the present application has the following beneficial effects:

[0046] In the technical solution of the present application, first, the target address information is obtained; secondly, the information type of the target address information is judged based on the information content included in the target address information; thirdly, the target address information is subjected to information supplement processing based on the information type to obtain first address information; then, a third-party API interface is called based on the first address information to obtain second address information and longitude and latitude coordinates; finally, the first address information, the second address information, and the longitude and latitude coordinates are integrated and redundant information is removed to obtain the improved target address information. It can be seen that in the technical solution of the present application, by obtaining the target address information, intelligently judging the information type, performing targeted supplement processing, and calling a third-party API to obtain more accurate address and longitude and latitude information, and finally integrating and removing redundancy, the improved address information is obtained. The efficiency and accuracy of address information improvement are significantly improved, and the overall quality of address information is enhanced. Description of the Drawings

[0047] To more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0048] Figure 1 Flowchart of a method for improving address information provided by an embodiment of the present application;

[0049] Figure 2 Flowchart of another method for improving address information provided by an embodiment of the present application;

[0050] Figure 3 Structural schematic diagram of a system for improving address information provided by an embodiment of the present application. Detailed implementation manners

[0051] As described above, the current address information processing means mainly rely on manual review and correction. This approach is both time-consuming and laborious, and it is difficult to effectively meet the needs of large-scale data processing. More seriously, the subjective judgment and differences in the manual review process often lead to inconsistent and frequently incorrect address information.

[0052] The inventor has proposed a method, system, device and storage medium for improving address information through research.

[0053] First, obtain the target address information; secondly, judge the information type of the target address information based on the information content included in the target address information; thirdly, perform information supplementation processing on the target address information based on the information type to obtain the first address information; then, call a third-party API interface based on the first address information to obtain the second address information and the longitude and latitude coordinates; finally, integrate and process the first address information, the second address information and the longitude and latitude coordinates, and remove redundant information to obtain the improved target address information. It can be seen that in the technical solution of the present application, by obtaining the target address information, intelligently judging the information type, performing targeted supplementation processing, calling a third-party API to obtain more accurate address and longitude and latitude information, and finally integrating and removing redundancy, the improved address information is obtained. The efficiency and accuracy of address information improvement are significantly improved, and the overall quality of address information is enhanced.

[0054] To enable those skilled in the art to better understand the solution of this application, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of this application.

[0055] It should be noted that the user information (including but not limited to user address information, user personal information, etc.) and data (including but not limited to data 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 need to comply with the relevant laws, regulations, and standards of relevant countries and regions.

[0056] See Figure 1 , which is a flowchart of a method for improving address information provided by an embodiment of this application. As Figure 1 shown, the method includes the following steps:

[0057] S101. Obtain target address information.

[0058] In the embodiment of this application, the target address information may be the address information to be improved filled in by the customer in any form such as an online form, an application program, or customer service.

[0059] In an optional implementation manner, before obtaining the target address information, the address information to be improved may be subjected to cleaning processing. The cleaning processing includes removing special characters, converting full-width characters to half-width characters, and standardizing spaces, etc.

[0060] In an example implementation, removing special characters can identify and remove all non-standard characters in the address information, such as punctuation marks (!, @, #, etc.), special symbols (※, ￥, €, etc.), and emoji, etc.; converting full-width characters to half-width characters can convert all full-width characters (such as Chinese punctuation marks, numbers, characters, etc.) in the address information to half-width characters; standardizing spaces can replace multiple consecutive spaces with a single space to ensure the format consistency of the address information.

[0061] In the embodiment of this application, the cleaned address information to be improved is used as the target address information. The target address information can be obtained in various ways. For example, it can be obtained by manual input of the user, extraction from a database, or by scanning a QR code, etc.

[0062] S102. Judge the information type of the target address information based on the information content included in the target address information.

[0063] In the embodiments of the present application, the target address information includes one or more types of information content. For example, address name information, provincial, municipal, county (district) coding information, postal code information, etc.

[0064] To facilitate the subsequent improvement of the target address information, the information type of the target address information can be determined based on the information content included in the target address information obtained in the previous step, so as to adopt different processing methods according to different information types.

[0065] In the embodiments of the present application, the information type indicates the integrity of the target address information, and the information type includes the first type, the second type, and the third type.

[0066] In the embodiments of the present application, the specific method for determining the information type of the target address information based on the information content included in the target address information includes:

[0067] When the target address information includes both address name information and provincial, municipal, county (district) coding information, it is determined that the information type of the target address information is the first type. For example, "No. 2, Building D, C County, A Province; [320000] B City, [321300] C County, [321323], A Province". In this case, there may be a lack of provincial, municipal, county (district) name information in the address name information, so it needs to be further supplemented and improved.

[0068] When the target address information includes address name information but does not include provincial, municipal, county (district) coding information, and the address name information includes provincial, municipal, county (district) name information, it is determined that the information type of the target address information is the second type. For example, "No. 2, Building D, C County, B City, A Province". In this case, the provincial, municipal, county (district) coding information is missing in the address information and needs to be supplemented through processing to be improved.

[0069] When the target address information includes address name information but does not include provincial, municipal, county (district) coding information, and the address name information does not include one or more of the provincial, municipal, county (district) name information, it is determined that the information type of the target address information is the third type. For example, "No. 2, Building D, C County, A Province". In this case, the address information is missing more, and the relevant information of the province, city, county (district) needs to be supplemented through the postal code or other means.

[0070] S103. Perform information supplementation processing on the target address information based on the information type to obtain the first address information.

[0071] In the embodiments of the present application, based on the determined information type, the corresponding information supplementation processing method is adopted to perform information supplementation processing on the target address information to obtain the first address information. The first address information obtained after the supplementation processing includes provincial, municipal, county (district) name information, address name information, and provincial, municipal, county (district) coding information.

[0072] It can be understood that this step supplements the missing information content in the target address information based on the information content included in the target address information.

[0073] In an example implementation, the missing provincial, municipal, county (district) coding information in the target address information can be supplemented by the address name information included in the target address information.

[0074] It should be noted that the provincial, municipal, county (district) coding in the embodiments of this application refers to a set of identification symbols arranged according to administrative divisions in compliance with the national standard of "Administrative Division Codes of the People's Republic of China" (GB / T 2260-2007). This set of codes uses six Arabic numerals to hierarchically represent the names of provinces (autonomous regions, municipalities directly under the Central Government), regions (cities, prefectures, leagues), and counties (districts, cities, banners) in China.

[0075] In the embodiments of this application, the target address information further includes postal code information. The specific method for performing information supplementation processing on the target address information based on the information type to obtain the first address information includes:

[0076] When the information type of the target address information is the first type, the provincial, municipal, county (district) name information is obtained based on the provincial, municipal, county (district) coding information, and the provincial, municipal, county (district) name information is supplemented into the target address information to obtain the first address information.

[0077] In an example implementation, the provincial, municipal, county (district) coding information can be obtained by transcoding the provincial, municipal, county (district) coding information.

[0078] When the information type of the target address information is the second type, the provincial, municipal, county (district) name information is parsed and obtained based on the address name information using a pre-trained language representation model, and the provincial, municipal, county (district) coding information is obtained based on the provincial, municipal, county (district) name information. The provincial, municipal, county (district) name information and the provincial, municipal, county (district) coding information are supplemented into the target address information to obtain the first address information.

[0079] When the information type of the target address information is the third type, the provincial, municipal, county (district) name information corresponding to the address name information is determined based on the postal code information in the address information using a pre-constructed postal code table, and the provincial, municipal, county (district) coding information is obtained based on the provincial, municipal, county (district) name information. The provincial, municipal, county (district) name information and the provincial, municipal, county (district) coding information are supplemented into the target address information to obtain the first address information.

[0080] S104. Call a third-party API interface based on the first address information to obtain the second address information and the longitude and latitude coordinates.

[0081] A third-party API interface refers to an Application Programming Interface (API) provided by a third-party service provider. These interfaces allow developers to integrate and use third-party services or data in their own applications or systems. In this way, developers can utilize the functions provided by the third party without having to build these functions from scratch, thus saving development time and resources.

[0082] In the embodiment of the present application, the third-party AIP interface refers to the third-party geocoding API interface.

[0083] Taking the first address information as input, the third-party geocoding API interface is called. These API interfaces parse and match according to the input first address information and return the more accurate second address information and the latitude and longitude coordinates corresponding to the target address information.

[0084] Among them, the second address information includes the name information of provinces, cities, counties (districts) and the community information corresponding to the target address information.

[0085] S105. Integrate and process the first address information, the second address information and the latitude and longitude coordinates, and remove redundant information to obtain the improved target address information.

[0086] In the embodiment of the present application, the first address information, the second address information and the latitude and longitude coordinates obtained in the foregoing steps are integrated and processed to remove redundant information.

[0087] In an example implementation, the first address information and the second address information are compared and analyzed, and all duplicate address information and descriptions are removed to ensure the uniqueness and conciseness of the final address information. The address information after duplicate removal is integrated with the latitude and longitude coordinates to obtain the improved target address information.

[0088] In the embodiment of the present application, the improved target address information includes address name information, province, city, county (district) coding information and latitude and longitude coordinates, where the address name information includes province, city, county (district) name information, street information and community information.

[0089] For example, the improved target address information is "No. 2, Building E, D Street, C County, B City, A Province; [320000] A Province, [321300] B City, [321323] C County; 118.675912, 33.709783".

[0090] In the embodiments of the present application, by obtaining target address information, intelligently judging the information type, performing targeted supplementary processing, and calling a third-party API to obtain more accurate address and longitude and latitude information, and finally integrating and removing redundancy, the improved address information is obtained. This significantly improves the efficiency and accuracy of address information improvement and enhances the overall quality of address information.

[0091] Optionally, the specific steps of the training method of the language representation model in step S103 include:

[0092] Step 1: Obtain training samples.

[0093] In the embodiments of the present application, the training samples include text data of address information and their corresponding annotation labels.

[0094] In an example implementation, the original address text can be obtained from a public data source or an enterprise internal database. Then, the BIOES annotation system is used to perform fine-grained annotation on address elements, generating a label sequence aligned with the original address text, and encapsulating the <address information text data, annotation label> pair after annotation into a training sample recognizable by the model.

[0095] Step 2: Preprocess the training samples and divide the preprocessed training samples into a training set, a validation set, and a test set.

[0096] In the embodiments of the present application, preprocessing the training samples includes removing noise data, standardizing the address format, etc. Then, the preprocessed data is divided into a training set, a validation set, and a test set for subsequent training and optimization of the model.

[0097] Step 3: Use a pre-encoder to convert the original text data into an input data format acceptable to the language representation model.

[0098] In the embodiments of the present application, the pre-encoder can be BERT or Word2Vec, etc. By using the pre-encoder, the original text data is converted into an input data format acceptable to the language representation model. For example, the address information is converted into word vectors or character vectors.

[0099] Step 4: Optimize the parameters of the language representation model based on the converted training set.

[0100] In the embodiments of the present application, the language representation model is trained based on the converted training set, and fine-tuning of parameter optimization is performed through the validation set to improve the performance of the language representation model in the address named entity recognition scenario.

[0101] In an example implementation, the cross-entropy loss function and the Adam optimizer can be used for model training.

[0102] Step 5: Evaluate the language representation model with optimized parameters based on model performance evaluation metrics, and further adjust and optimize the parameters of the language representation model according to the evaluation results.

[0103] In the embodiments of the present application, evaluate the trained model based on model performance evaluation metrics (such as accuracy, recall rate, F1 value), and further adjust and optimize the model parameters according to the evaluation results.

[0104] Optionally, the specific steps of the method for constructing the pre-built postal code table in step S103 include:

[0105] Step 1: Obtain the mapping relationship between street postal codes and provinces, municipalities, counties (districts).

[0106] In the embodiments of the present application, the mapping relationship between street postal codes and provinces, municipalities, counties (districts) can be obtained from the postal department or public data sources. For example, it is obtained that "100080" corresponds to "Haidian District, Beijing" and "200030" corresponds to "Xuhui District, Shanghai".

[0107] Step 2: Construct a postal code table containing street postal codes and corresponding province, municipality, county (district) information according to the mapping relationship.

[0108] In an example implementation, the postal code table is shown in Table 1.

[0109] Table 1

[0110]

[0111]

[0112] Optionally, the postal code table can be updated and maintained regularly to ensure its accuracy and integrity. For example, when the postal code of a certain area changes, the corresponding information in the postal code table needs to be updated in a timely manner.

[0113] Figure 2 This is another flowchart of the address information improvement method provided by the embodiments of the present application. In the embodiments introduced through this figure, a more detailed description is provided for the implementation of the address information improvement method.

[0114] Such as Figure 2 The address information improvement method shown includes the following steps:

[0115] S201: Obtain the target address information.

[0116] S202: Determine the information type of the target address information based on the information content included in the target address information.

[0117] S203. Perform information supplementation processing on the target address information based on the information type to obtain the first address information.

[0118] The implementation manners of S201 - S203 are basically the same as those of S101 - S103 in the method embodiments introduced above, and will not be elaborated here. For the relevant technical implementations, reference can be made to the introduction of S101 - S103 above.

[0119] S204. Remove the maximum repeated string from the first address information to obtain the first address information after duplicate removal processing.

[0120] In the embodiments of the present application, since there may be duplicate redundant address information in the first address information after supplementation processing, it is necessary to perform the processing of removing the maximum repeated string on the first address information.

[0121] In an example implementation manner, the string can be split first to find the longest repeated substring. Algorithms such as dynamic programming or suffix arrays can be used to find the repeated substring. After determining the repeated substring, it is deleted from the original string, but only one complete repeated part is deleted to retain one instance.

[0122] S205. Call the third - party API interface based on the first address information after duplicate removal processing to obtain the second address information and the longitude and latitude coordinates.

[0123] In the embodiments of the present application, the third - party API interface can be called by sending a request to the third - party API using an HTTP request library (such as the requests library in Python, HttpURLConnection in Java, etc.).

[0124] In an alternative implementation manner, the status code of the API response can be checked to ensure a successful call. Then, the JSON - formatted content in the response data is parsed to extract the second address information and the longitude and latitude coordinates. The second address information can be an address after standardization and formatting, and the longitude and latitude coordinates are the geographical coordinates corresponding to the address.

[0125] S206. Integrate the first address information, the second address information, and the longitude and latitude coordinates, and remove redundant information to obtain the improved target address information.

[0126] The implementation manner of S206 is basically the same as that of S105 in the method embodiments introduced above, and will not be elaborated here. For the relevant technical implementations, reference can be made to the introduction of S105 above.

[0127] S207. Convert the longitude and latitude coordinates into a comparable string code based on the spatial index algorithm.

[0128] A spatial index algorithm is an algorithm used to organize spatial data for fast retrieval and query.

[0129] In an alternative implementation, taking the GeoHash algorithm as an example, the latitude and longitude coordinates (such as 40.222012, 116.248283) can be converted into a string encoding. The specific steps include:

[0130] S2071: Divide and encode the latitude range (-90, 90) and longitude range (-180, 180) respectively.

[0131] S2072: Combine the binary encodings of latitude and longitude, with the odd bits for latitude and the even bits for longitude.

[0132] S2073: Convert the final binary string into a base32 encoding to obtain a comparable string encoding (such as wx4sv61q).

[0133] In the embodiments of the present application, by converting the latitude and longitude coordinates into a string encoding, the comparison and sorting characteristics of the string can be utilized to quickly find the target area or adjacent points.

[0134] S208: Grid the refined target address information based on the string encoding.

[0135] In the embodiments of the present application, for the convenience of spatial analysis and data aggregation, the refined target address information can be gridded.

[0136] In an exemplary implementation, taking the GeoHash string encoding as an example, the steps of gridding the refined target address information specifically include:

[0137] According to the prefix length of the GeoHash encoding (such as the first 4 bits, the first 5 bits, etc.), the refined target address information is divided into different grid cells. GeoHash encodings with the same prefix address information will be classified into the same grid.

[0138] In an alternative implementation, after gridding the address information, the address of the center point of the grid can be retrieved through a third-party API interface to obtain the customer distribution within each address grid range.

[0139] In the embodiments of the present application, through intelligent differential supplementation processing, it is possible to effectively complete missing information such as the names and codes of provinces, cities, counties (districts), etc., and combine with third-party API interfaces to obtain standardized second address information and accurate longitude and latitude coordinates, significantly improving the integrity and accuracy of address information. Secondly, by removing the largest repeated strings, redundant information is reduced, optimizing data storage and processing efficiency. In addition, using a spatial index algorithm to convert longitude and latitude coordinates into string codes and performing grid processing based on the codes can quickly divide address information into manageable grid cells, facilitating spatial analysis, data aggregation, and proximity point queries, and improving the efficiency of services such as customer distribution analysis. At the same time, by calling third-party API interfaces, it is compatible with various data sources and geographic information services, and has strong scalability and flexibility. Through the above technical solutions, address information can be automatically improved and standardized, reducing the workload of manual input and correction.

[0140] Based on the address information improvement method provided in the foregoing embodiments, correspondingly, the present application also provides an address information improvement system. Figure 3 As shown in the structure diagram of an address information improvement system provided by an embodiment of the present application. Figure 3 As shown, the address information improvement system includes: an address acquisition module 301, a type judgment module 302, an address supplementation module 303, an API call module 304, and an address improvement module 305.

[0141] The address acquisition module 301 is used to acquire target address information; the target address information is the address information to be improved.

[0142] The type judgment module 302 is used to judge the information type of the target address information based on the information content included in the target address information.

[0143] The address supplementation module 303 is used to perform information supplementation processing on the target address information based on the information type to obtain first address information.

[0144] The API call module 304 is used to call a third-party API interface based on the first address information to obtain second address information and longitude and latitude coordinates.

[0145] The address improvement module 305 is used to integrate the first address information, the second address information, and the longitude and latitude coordinates, and remove redundant information to obtain the improved target address information.

[0146] In the embodiments of the present application, the address acquisition module 301, the type judgment module 302, the address supplementation module 303, the API call module 304, and the address improvement module 305 in the address information improvement system work together, significantly improving the efficiency and accuracy of address information improvement and enhancing the overall quality of address information.

[0147] In an alternative implementation, the API call module 304 includes:

[0148] A deduplication sub-module for removing the maximum repeated string from the first address information to obtain the deduplicated first address information.

[0149] A call sub-module for calling a third-party API interface based on the deduplicated first address information to obtain second address information and longitude and latitude coordinates.

[0150] In an alternative implementation, the information type includes a first type, a second type, and a third type.

[0151] The type judgment module 302 is specifically configured to:

[0152] When the target address information contains both address name information and province / city / county (district) code information, determine that the information type of the target address information is the first type;

[0153] When the target address information contains address name information but does not contain province / city / county (district) code information, and the address name information contains province / city / county (district) name information, determine that the information type of the target address information is the second type;

[0154] When the target address information contains address name information but does not contain province / city / county (district) code information, and the address name information does not contain one or more of the province / city / county (district) name information, determine that the information type of the target address information is the third type.

[0155] In an alternative implementation, the target address information includes postal code information. The address supplement module 303 is specifically configured to:

[0156] When the information type is the first type, obtain province / city / county (district) name information based on the province / city / county (district) code information, and supplement the province / city / county (district) name information to the target address information to obtain the first address information;

[0157] When the information type is the second type, parse and obtain province / city / county (district) name information based on the address name information using a pre-trained language representation model, obtain province / city / county (district) code information based on the province / city / county (district) name information, and supplement the province / city / county (district) name information and the province / city / county (district) code information to the target address information to obtain the first address information;

[0158] When the information type is the third type, based on the postal code information in the address information, use the pre-constructed postal code table to determine the name information of the province, city, county (district) corresponding to the address name information, and obtain the province, city, county (district) code information based on the name information of the province, city, county (district). Supplement the name information of the province, city, county (district) and the province, city, county (district) code information to the target address information to obtain the first address information.

[0159] Optionally, the address information improvement system further includes:

[0160] A postal code table construction module, configured to obtain the mapping relationship between the street postal code and the province, city, county (district). According to the mapping relationship, construct a postal code table including the street postal code and the corresponding province, city, county (district) information.

[0161] Optionally, the address information improvement system further includes:

[0162] A model training module, configured to obtain training samples; the training samples include address information text data and their corresponding annotation labels; preprocess the training samples, and divide the preprocessed training samples into a training set, a validation set, and a test set; use a pre-encoder to convert the original text data into an input data format acceptable to the language representation model; optimize the parameters of the language representation model based on the converted training set; evaluate the parameter-optimized language representation model based on model performance evaluation metrics, and further adjust and optimize the parameters of the language representation model according to the evaluation results.

[0163] Optionally, the address information improvement system further includes:

[0164] A coordinate conversion module, configured to convert the longitude and latitude coordinates into comparable string codes based on a spatial indexing algorithm.

[0165] An address gridification module, configured to gridify the improved target address information based on the string codes.

[0166] In addition, an embodiment of the present application further provides an address information improvement device, and the device includes a processor and a memory.

[0167] The memory is used to store program codes and transmit the program codes to the processor;

[0168] The processor is configured to execute the steps of address information improvement described in any one of the above method embodiments according to the instructions in the program codes.

[0169] In addition, an embodiment of the present application further provides a computer-readable storage medium, in which a computer program is stored. When the program is run by a processor, the address information improvement method introduced in any manner of the method embodiment is implemented.

[0170] It should be noted that the various embodiments in this specification are described in a progressive manner. For the same or similar parts among the various embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the device and system embodiments, since they are basically similar to the method embodiments, the description is relatively simple. For the relevant parts, reference can be made to the partial description of the method embodiments. The device and system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated. The components prompted as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. A person of ordinary skill in the art can understand and implement it without creative work.

[0171] As mentioned above, this is only a specific implementation manner of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for improving address information, characterized in that Including: Obtain target address information; Judge the information type of the target address information based on the information content included in the target address information; Perform information supplementation processing on the target address information based on the information type to obtain the first address information; Call a third-party API interface based on the first address information to obtain the second address information and the latitude and longitude coordinates; Integrate the first address information, the second address information, and the latitude and longitude coordinates, and remove redundant information to obtain the improved target address information.

2. The method according to claim 1, wherein The calling of the third-party API interface based on the first address information to obtain the second address information and the latitude and longitude coordinates includes: Remove the maximum repeated string from the first address information to obtain the first address information after duplicate removal processing; Call a third-party API interface based on the first address information after duplicate removal processing to obtain the second address information and the latitude and longitude coordinates.

3. The method according to claim 1, characterized in that The information type includes the first type, the second type, and the third type; the judging of the information type of the target address information based on the information content included in the target address information includes: When the target address information includes both the address name information and the provincial, municipal, county (district) coding information, determine that the information type of the target address information is the first type; When the target address information includes the address name information but does not include the provincial, municipal, county (district) coding information, and the address name information includes the provincial, municipal, county (district) name information, determine that the information type of the target address information is the second type; When the target address information includes the address name information but does not include the provincial, municipal, county (district) coding information, and the address name information does not include one or more of the provincial, municipal, county (district) name information, determine that the information type of the target address information is the third type.

4. The method according to claim 3, characterized in that The target address information includes postal code information; the performing of information supplementation processing on the target address information based on the information type to obtain the first address information includes: When the information type is the first type, obtain the provincial, municipal, county (district) name information based on the provincial, municipal, county (district) coding information, and supplement the provincial, municipal, county (district) name information to the target address information to obtain the first address information; When the information type is the second type, parse and obtain the provincial, municipal, county (district) name information based on the address name information using a pre-trained language representation model, and obtain the provincial, municipal, county (district) coding information based on the provincial, municipal, county (district) name information, and supplement the provincial, municipal, county (district) name information and the provincial, municipal, county (district) coding information to the target address information to obtain the first address information; When the information type is the third type, determine the provincial, municipal, county (district) name information corresponding to the address name information based on the postal code information in the address information using a pre-constructed postal code table, and obtain the provincial, municipal, county (district) coding information based on the provincial, municipal, county (district) name information, and supplement the provincial, municipal, county (district) name information and the provincial, municipal, county (district) coding information to the target address information to obtain the first address information.

5. The method according to claim 4, wherein The construction method of the pre-constructed postal code table includes: Obtain the mapping relationship between street postal codes and provinces, cities, counties (districts); Construct a postal code table containing street postal codes and corresponding province, city, county (district) information according to the mapping relationship.

6. The method according to claim 4, characterized in that, The training method of the language representation model includes: Obtain training samples; the training samples include address information text data and their corresponding annotation labels; Preprocess the training samples and divide the preprocessed training samples into a training set, a validation set, and a test set; Use a pre-encoder to convert the original text data into an input data format acceptable to the language representation model; Optimize the parameters of the language representation model based on the converted training set; Evaluate the language representation model with optimized parameters based on model performance evaluation metrics, and further adjust and optimize the parameters of the language representation model according to the evaluation results.

7. The method according to claim 1, wherein The method further includes: Convert the longitude and latitude coordinates into comparable string codes based on a spatial indexing algorithm; Grid the improved target address information based on the string codes.

8. An address information improvement system, characterized in that, The system includes: An address acquisition module for acquiring target address information; the target address information is the address information to be improved; A type judgment module for judging the information type of the target address information based on the information content included in the target address information; An address supplement module for performing information supplement processing on the target address information based on the information type to obtain first address information; An API call module for calling a third-party API interface based on the first address information to obtain second address information and longitude and latitude coordinates; An address improvement module for integrating the first address information, the second address information, and the longitude and latitude coordinates, and removing redundant information to obtain improved target address information.

9. An address information improvement device, characterized in that, Includes: A processor and a memory: The memory is used to store program code and transmit the program code to the processor; The processor is used to execute the steps of the address information improvement method according to any one of claims 1 to 7 based on the instructions in the program code.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store program code, and the program code is used to execute the steps of the address information improvement method according to any one of claims 1 to 7.

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