CN116932935A - Address matching method, device, equipment, medium and program product - Google Patents
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Abstract
The present application relates to an address matching method, apparatus, device, medium and program product. The method comprises the following steps: firstly, obtaining a target address which needs to be subjected to address matching, obtaining a standard address pool which comprises a plurality of standard addresses, then calculating longitude and latitude difference degrees of the target address and each standard address, determining a plurality of candidate standard addresses from the standard address pool according to the calculated longitude and latitude difference degrees, finally, calculating text similarity of the target address and each candidate standard address, and determining a standard address which is matched with the target address from the plurality of candidate standard addresses according to the calculated text similarity. The method can improve the efficiency of the address matching process.
Description
Technical Field
The present application relates to the field of computer technologies, and in particular, to an address matching method, apparatus, device, medium, and program product.
Background
With the development of broadband technology, the network demands of users are increasing, and the addresses of users need to be checked and matched in broadband service acceptance and network planning, but currently existing address resources of users are difficult to open due to unmatched with standard addresses, and network planning is inaccurate, so that the existing address resources need to be matched with the standard address resources, and the existing address resources are converted into the standard address resources.
In the existing address matching method, when the number of matching is large, the matching speed is relatively slow.
Disclosure of Invention
In view of the foregoing, it is desirable to provide an address matching method, apparatus, device, medium, and program product that can match efficiently.
In a first aspect, the present application provides an address matching method. The method comprises the following steps: obtaining a target address which needs to be subjected to address matching, and obtaining a standard address pool, wherein the standard address pool comprises a plurality of standard addresses; calculating longitude and latitude difference degrees of the target address and each standard address, and determining a plurality of candidate standard addresses from a standard address pool according to the calculated longitude and latitude difference degrees; and calculating the text similarity between the target address and each candidate standard address, and determining the standard address matched with the target address from the plurality of candidate standard addresses according to the calculated text similarity.
In one embodiment, before obtaining the standard address pool, the method further comprises: if a first standard address which lacks the longitude and latitude information exists in the standard address pool, determining the longitude and latitude information of the first standard address according to a second standard address which comprises the longitude and latitude information in the standard address pool.
In one embodiment, determining the latitude and longitude information of the first standard address according to the second standard address including the latitude and longitude information in the standard address pool includes: calculating the text similarity between the first standard address and each second standard address, and determining a target standard address from the plurality of second standard addresses according to the calculated text similarity; and determining the same kind of standard addresses clustered into the same kind of cluster with the target standard addresses from the standard address pool, and determining the longitude and latitude information of the first standard address according to the longitude and latitude information of the same kind of standard addresses.
In one embodiment, before determining the homogeneous standard addresses clustered into the same class cluster with the target standard address from the standard address pool, the method further comprises: and clustering the second standard addresses according to the DBSCAN algorithm to obtain a plurality of class clusters.
In one embodiment, determining the latitude and longitude information of the first standard address according to the latitude and longitude information of the same type of standard address includes: and determining the longitude and latitude information of the first standard address according to the average value of the longitude and latitude information of the same kind of standard addresses.
In one embodiment, calculating the latitude and longitude difference between the target address and each standard address includes: and calculating the Euclidean distance between the target address and each standard address, and taking the Euclidean distance obtained by calculation as the longitude and latitude difference degree.
In one embodiment, calculating the text similarity of the target address and each candidate standard address includes: word segmentation is carried out on the target address and each candidate standard address, and a word vector of the target address and a word vector of each candidate standard address are generated; and calculating cosine similarity of the word vector of the target address and the word vector of each candidate standard address, and taking the calculated cosine similarity as text similarity of the target address and each candidate standard address.
In one embodiment, determining a plurality of candidate standard addresses from the standard address pool according to the calculated longitude and latitude difference comprises: and taking N standard addresses with the smallest longitude and latitude difference degree as candidate standard addresses, wherein N is a positive integer.
In one embodiment, determining a standard address matching the target address from a plurality of candidate standard addresses according to the calculated text similarity includes: if the maximum value in the text similarity is greater than or equal to a preset threshold value, the candidate standard address with the highest text similarity is used as the standard address matched with the target address; if the maximum value in the text similarity is smaller than a preset threshold value, M standard addresses with the smallest longitude and latitude difference degrees are used as candidate standard addresses, and the step of calculating the text similarity between the target address and each candidate standard address is carried out in a returning mode, wherein M is a positive integer larger than N.
In a second aspect, the application further provides an address matching device. The device comprises:
the system comprises an acquisition module, a storage module and a storage module, wherein the acquisition module is used for acquiring a target address which needs to be subjected to address matching and acquiring a standard address pool, and the standard address pool comprises a plurality of standard addresses;
the first calculation module is used for calculating the longitude and latitude difference degrees of the target address and each standard address, and determining a plurality of candidate standard addresses from the standard address pool according to the calculated longitude and latitude difference degrees;
and the second calculation module is used for calculating the text similarity between the target address and each candidate standard address and determining the standard address matched with the target address from the plurality of candidate standard addresses according to the calculated text similarity.
In one embodiment, the system further includes a determining module, configured to determine, if a first standard address that lacks the latitude and longitude information exists in the standard address pool, the latitude and longitude information of the first standard address according to a second standard address that includes the latitude and longitude information in the standard address pool.
In one embodiment, the determining module is specifically configured to calculate a text similarity between the first standard address and each second standard address, and determine a target standard address from the plurality of second standard addresses according to the calculated text similarity; and determining the same kind of standard addresses clustered into the same kind of cluster with the target standard addresses from the standard address pool, and determining the longitude and latitude information of the first standard address according to the longitude and latitude information of the same kind of standard addresses.
In one embodiment, the method further includes a clustering module, configured to perform clustering processing on the plurality of second standard addresses according to a DBSCAN algorithm, to obtain a plurality of class clusters.
In one embodiment, the determining module is specifically configured to determine the latitude and longitude information of the first standard address according to an average value of latitude and longitude information of similar standard addresses.
In one embodiment, the first calculation module is specifically configured to calculate a euclidean distance between the target address and each standard address, and use the calculated euclidean distance as the longitude and latitude difference degree.
In one embodiment, the second computing module is configured to perform word segmentation on the target address and each candidate standard address, and generate a word vector of the target address and a word vector of each candidate standard address; and calculating cosine similarity of the word vector of the target address and the word vector of each candidate standard address, and taking the calculated cosine similarity as text similarity of the target address and each candidate standard address.
In one embodiment, the first calculation module is specifically configured to use N standard addresses with minimum degrees of longitude and latitude difference as candidate standard addresses, where N is a positive integer.
In one embodiment, the second calculating module is specifically configured to, if a maximum value in the text similarity is greater than or equal to a preset threshold, use a candidate standard address with the highest text similarity as a standard address matched with the target address; if the maximum value in the text similarity is smaller than a preset threshold value, M standard addresses with the smallest longitude and latitude difference degrees are used as candidate standard addresses, and the step of calculating the text similarity between the target address and each candidate standard address is carried out in a returning mode, wherein M is a positive integer larger than N.
In a third aspect, the present application also provides a computer device. The computer device comprises a memory storing a computer program and a processor implementing the address matching method of any of the above first aspects when executing the computer program.
In a fourth aspect, the present application also provides a computer-readable storage medium. The computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the address matching method of any of the above first aspects.
In a fifth aspect, the present application also provides a computer program product. The computer program product comprises a computer program which, when executed by a processor, implements the address matching method of any of the above first aspects.
The address matching method, the device, the equipment, the medium and the program product comprise the steps of firstly, obtaining a target address to be subjected to address matching, obtaining a standard address pool comprising a plurality of standard addresses, then, calculating longitude and latitude difference degrees of the target address and each standard address, determining a plurality of candidate standard addresses from the standard address pool according to the calculated longitude and latitude difference degrees, finally, calculating text similarity of the target address and each candidate standard address, and determining the standard address matched with the target address from the plurality of candidate standard addresses according to the calculated text similarity. In this way, preliminary screening is performed according to the longitude and latitude difference, a plurality of candidate standard addresses are determined in a standard address pool, further screening is performed according to the text similarity, and standard addresses matched with target addresses are determined in the plurality of candidate standard addresses.
Drawings
FIG. 1 is a flow chart of an address matching method in one embodiment;
FIG. 2 is a flow chart of an address matching method according to another embodiment;
FIG. 3 is a flow chart of an address matching method according to another embodiment;
FIG. 4 is a flow chart of an address matching method according to another embodiment;
FIG. 5 is a flowchart of an address matching method according to another embodiment;
FIG. 6 is a block diagram of an address matching method in another embodiment;
FIG. 7 is a block diagram of an address matching device in one embodiment;
fig. 8 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
At present, because the user address resource is not matched with the standard address in the history, the network service is difficult to open and the network planning is inaccurate, so that the existing address resource is matched with the standard address resource, and the existing address resource is converted into the standard address resource. In the conventional address matching method, when the number of matches is large, the matching speed is relatively slow.
Based on the above conventional technology, the address matching method provided by the embodiment of the application obtains the target address to be subjected to address matching, obtains the standard address pool including a plurality of standard addresses, calculates the longitude and latitude difference between the target address and each standard address, determines a plurality of candidate standard addresses from the standard address pool according to the calculated longitude and latitude difference, calculates the text similarity between the target address and each candidate standard address, and determines the standard address matched with the target address from the plurality of candidate standard addresses according to the calculated text similarity. In this way, preliminary screening is performed according to the longitude and latitude difference, a plurality of candidate standard addresses are determined in a standard address pool, further screening is performed according to the text similarity, and standard addresses matched with target addresses are determined in the plurality of candidate standard addresses.
It should be noted that the beneficial effects or the technical problems to be solved by the embodiments of the present application are not limited to this one, but may be other implicit or related problems, and particularly, reference may be made to the following description of embodiments.
The following describes the technical scheme of the present application and how the technical scheme of the present application solves the above technical problems in detail with specific embodiments. The following embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.
In one embodiment, as shown in fig. 1, an address matching method is provided, where the method is applied to a terminal for illustration, it is understood that the method may also be applied to a server, and may also be applied to a system including the terminal and the server, and implemented through interaction between the terminal and the server. The method comprises the following steps:
step 101, obtaining a target address which needs to be subjected to address matching, and obtaining a standard address pool.
Wherein the standard address pool comprises a plurality of standard addresses. The target address is an address to be matched, and in order to perform standardization processing on the target address, the target address needs to be matched with a standard address in a standard address pool, namely, a standard address corresponding to the target address is determined.
Step 102, calculating the longitude and latitude difference between the target address and each standard address, and determining a plurality of candidate standard addresses from the standard address pool according to the calculated longitude and latitude difference.
The target address and each standard address can contain longitude and latitude information, longitude and latitude difference degrees of the target address and each standard address are calculated, wherein the longitude and latitude difference degrees can indicate the distance between the target address and each standard address, the higher the longitude and latitude difference degrees are, the farther the distance between the target address and the standard address is, and the lower the longitude and latitude difference degrees are, the closer the distance between the target address and the standard address is. Alternatively, the longitude and latitude difference degree can be calculated by the difference between the longitude and latitude of the two addresses, or by calculating the distance between the two addresses. Then, a plurality of standard addresses are selected from the standard resource pool as candidate standard addresses through the longitude and latitude difference degree obtained through calculation, wherein the candidate standard addresses can be addresses close to the target address, alternatively, an integral number of standard addresses with the smallest longitude and latitude difference degree can be selected as candidate standard addresses, and the candidate standard addresses are the integral number of standard addresses closest to the target address in the standard address pool.
And 103, calculating the text similarity between the target address and each candidate standard address, and determining the standard address matched with the target address from a plurality of candidate standard addresses according to the calculated text similarity.
After screening the plurality of candidate standard addresses, calculating the text similarity between the target address and each candidate standard address, wherein the text similarity can be used for indicating the similarity degree between the target address and the text of the candidate standard address. The higher the text similarity, i.e. the higher the similarity of the target address and the candidate standard address. Alternatively, the text similarity calculating method may calculate the cosine distance, the euclidean distance, or the hamming distance. After the text similarity between the target address and each candidate standard address is calculated, optionally, the candidate standard address with the highest text similarity may be selected as the standard address matched with the target address.
In the above embodiment, first, a target address to be subjected to address matching is obtained, a standard address pool including a plurality of standard addresses is obtained, then, longitude and latitude difference degrees of the target address and each standard address are calculated, a plurality of candidate standard addresses are determined from the standard address pool according to the calculated longitude and latitude difference degrees, finally, text similarity between the target address and each candidate standard address is calculated, and a standard address matched with the target address is determined from the plurality of candidate standard addresses according to the calculated text similarity. In this way, preliminary screening is performed according to the longitude and latitude difference, a plurality of candidate standard addresses are determined in a standard address pool, further screening is performed according to the text similarity, and standard addresses matched with target addresses are determined in the plurality of candidate standard addresses.
In one embodiment, because some standard addresses in the standard address pool may have a problem of missing longitude and latitude information, before obtaining the standard address pool, the longitude and latitude information needs to be filled in the standard addresses missing the longitude and latitude information, including: if a first standard address which lacks the longitude and latitude information exists in the standard address pool, determining the longitude and latitude information of the first standard address according to a second standard address which comprises the longitude and latitude information in the standard address pool.
The second standard addresses may be multiple, the second standard addresses include longitude and latitude information, and the longitude and latitude information of the first standard address may be determined by the longitude and latitude information of the second standard addresses, for example, the longitude and latitude information of a second standard address closest to the first standard address in the multiple second standard addresses is used as the longitude and latitude information of the first standard address.
Optionally, the step of determining the latitude and longitude information of the first standard address according to the second standard address including the latitude and longitude information in the standard address pool may further include, as shown in fig. 2:
step 201, calculating the text similarity between the first standard address and each second standard address, and determining the target standard address from the plurality of second standard addresses according to the calculated text similarity.
In order to determine the latitude and longitude information of the first standard address, the target standard address closest to the first standard address is first determined. Word segmentation is carried out on the text of the first standard address and each text of the second standard address respectively to form a plurality of word vectors, and then cosine distances between the word vectors of the first standard address and the word vectors of each second standard address are calculated to obtain the text similarity of the first standard address and each second standard address. And then taking the second standard address with highest text similarity as a target standard address.
Step 202, determining the same kind of standard addresses clustered into the same kind of cluster with the target standard addresses from the standard address pool, and determining the longitude and latitude information of the first standard address according to the longitude and latitude information of the same kind of standard addresses.
After the target standard address is determined, the standard address pool is classified by a clustering algorithm, and the similar standard addresses, namely the standard addresses of the same class of clusters as the target standard address after classification, are optionally determined according to the average value of the longitude and latitude information of the similar standard addresses. I.e. the average value of the longitude and the average value of the latitude of the same class standard address is taken as the longitude and the latitude of the first standard address.
Optionally, the clustering algorithm may be a DBSCAN algorithm, and the clustering processing is performed on the plurality of second standard addresses according to the DBSCAN algorithm, so as to obtain a plurality of class clusters. For example, by using the density reachable property of the DBSCAN algorithm, the latitude and longitude information of the target standard address is used as a center point, and then all points with a distance of Eps (Eps-neighborhood of a point, field radius) or less from the center point are found. If the number of data points within Eps from the center point is less than min_samples (the minimum number of points within the radius of the field that becomes the core sample), then the center point is marked as noise. If the number of data points within the Eps is greater than min samples, the center point is marked as a core sample. All neighbors within the distance Eps of the access center point are then assigned a new cluster label created if not already assigned a cluster, to the accessed neighbor. If the neighbor is a core sample, then its neighbors are accessed sequentially, and so on. The clusters are gradually increased until there are no more core samples within the Eps distance of the cluster, resulting in a plurality of class clusters.
According to the embodiment, the longitude and latitude of the first standard address with missing longitude and latitude information is determined through the second standard address comprising longitude and latitude information in the standard address pool, so that the problem that part of standard addresses possibly existing in the standard address pool are missing in longitude and latitude is solved, and the accuracy of address matching is improved.
In one embodiment, calculating the latitude and longitude difference between the target address and each standard address includes: and calculating the Euclidean distance between the target address and each standard address, and taking the Euclidean distance obtained by calculation as the longitude and latitude difference degree. The Euclidean distance between the longitude and latitude of the target address and the longitude and latitude of each standard address is calculated, and the calculation formula of the longitude and latitude difference is as follows:
longitude and latitude difference = sqrt ((x 1-x 2) 2 +(y1-y2) 2 )
Wherein x1 and x2 are latitude values of the target address and the standard address, and y1 and y2 are precision values of the target address and the standard address.
In an embodiment of the present application, determining a plurality of candidate standard addresses from a standard address pool according to the calculated longitude and latitude difference, includes: and taking N standard addresses with the smallest longitude and latitude difference degree as candidate standard addresses, wherein N is a positive integer.
Optionally, N standard addresses with the smallest latitude and longitude difference degree, that is, N standard addresses nearest to the latitude and longitude of the target address are selected as candidate standard addresses, where N may be 300. Therefore, the calculation of text similarity between the target address and all standard addresses in the standard address pool is not needed, and the calculation speed is faster.
In the above embodiment, the calculation of the longitude and latitude difference is the calculation between two values, compared with the calculation of the similarity with the text, the calculation speed is faster, so that the candidate standard addresses with the longitude and latitude close to each other are firstly screened out, and then the next calculation is performed, so that the efficiency of address matching can be improved.
In the embodiment of the present application, after the preliminary screening, the step of calculating the text similarity between the target address and each candidate standard address, as shown in fig. 2, includes:
step 301, word segmentation is performed on the target address and each candidate standard address, so as to generate a word vector of the target address and a word vector of each candidate standard address.
And carrying out word segmentation processing on the target address and each candidate standard address, and generating a word vector of the target address and a word vector of each candidate standard address according to word Frequency or TF-IDF (Term Frequency-inverse document Frequency).
Step 302, calculating cosine similarity between the word vector of the target address and the word vector of each candidate standard address, and taking the calculated cosine similarity as text similarity between the target address and each candidate standard address.
And carrying out cosine similarity calculation on the word vector of the target address and the word vector of each candidate standard address to obtain the text similarity of the target address and each candidate address. Optionally, the step of determining, from the plurality of candidate standard addresses, a standard address matching the target address according to the text similarity, as shown in fig. 4, includes:
and step 401, if the maximum value in the text similarity is greater than or equal to a preset threshold value, the candidate standard address with the highest text similarity is used as the standard address matched with the target address.
The preset threshold value can be set according to actual requirements, and when the text similarity is greater than or equal to the preset threshold value, the two addresses can be determined to be matched. Therefore, when the maximum value of the calculated plurality of text similarities between the target address and each candidate standard address is greater than or equal to a preset threshold value, the candidate standard address with the highest text similarity is the standard address matched with the target address.
And step 402, if the maximum value in the text similarity is smaller than a preset threshold value, taking M standard addresses with the smallest longitude and latitude difference as candidate standard addresses, and returning to the step of executing the calculation of the text similarity between the target address and each candidate standard address, wherein M is a positive integer larger than N.
If the maximum value of the plurality of text similarity is smaller than the preset threshold, at this time, no standard address which accords with the matching condition with the target address exists in the determined candidate standard addresses, that is, the cluster mean deviation is larger, the selection range of the candidate standard addresses needs to be enlarged, that is, M standard addresses with the smallest longitude and latitude difference degree are selected as candidate standard addresses, M is larger than N, that is, is larger than 300, and the selectable M can be 1000.
And then, continuing to calculate the text similarity between the target address and each candidate address, if the maximum value in the calculated text similarity is greater than a preset threshold value, then, setting the candidate standard address with the highest text similarity as the standard address matched with the target address, if the candidate standard address is still smaller than the preset threshold value, continuing to increase the screening range according to the longitude and latitude information, namely increasing the value of M, and optionally taking 2000 by M until the maximum value in the calculated text similarity exceeds the preset threshold value.
In the above embodiment, when the cluster mean deviation is smaller, that is, the maximum value in the text similarity is greater than the preset threshold, the standard address matched with the target address can be determined through a small-range search, so that the calculated amount is reduced, when the cluster mean deviation is greater, that is, the maximum value in the text similarity is smaller than the preset threshold, the selection range of the candidate standard address is enlarged, a large-range search is performed, the matching accuracy is improved, meanwhile, the search range is determined through the screening of longitude and latitude difference, and the matching speed can be improved when the data size of the standard address pool is huge.
In an embodiment of the present application, please refer to fig. 5, which shows a flowchart of an address matching method according to an embodiment of the present application, the address matching method includes the following steps:
In step 501, if a first standard address with missing latitude and longitude information exists in the standard address pool, the latitude and longitude information of the first standard address is determined according to a second standard address including the latitude and longitude information in the standard address pool.
And calculating the text similarity between the first standard address and each second standard address, and determining the target standard address from the plurality of second standard addresses according to the calculated text similarity.
And determining the same kind of standard addresses clustered into the same kind of cluster with the target standard addresses from the standard address pool, and determining the longitude and latitude information of the first standard address according to the longitude and latitude information of the same kind of standard addresses.
Step 502, obtaining a target address required to be subjected to address matching, and obtaining a standard address pool.
In step 503, the latitude and longitude difference between the target address and each standard address is calculated, and a plurality of candidate standard addresses are determined from the standard address pool according to the calculated latitude and longitude difference.
And taking N standard addresses with the smallest longitude and latitude difference degree as candidate standard addresses, wherein N is a positive integer.
Step 504, word segmentation is performed on the target address and each candidate standard address, so as to generate a word vector of the target address and a word vector of each candidate standard address.
In step 505, the cosine similarity between the word vector of the target address and the word vector of each candidate standard address is calculated, and the calculated cosine similarity is used as the text similarity between the target address and each candidate standard address.
And step 506, if the maximum value in the text similarity is greater than or equal to the preset threshold value, the candidate standard address with the highest text similarity is used as the standard address matched with the target address.
And step 507, if the maximum value in the text similarity is smaller than a preset threshold value, taking M standard addresses with the smallest longitude and latitude difference as candidate standard addresses, and returning to the step of executing the calculation of the text similarity between the target address and each candidate standard address, wherein M is a positive integer larger than N.
For the convenience of the reader to understand the technical solution provided by the embodiment of the present application, the address matching method of the present application is illustrated, please refer to fig. 6, fig. 6 is a functional block diagram of the address matching method. The address matching method can comprise a word segmentation module, a text similarity calculation module, a text similarity judgment module, a longitude and latitude small-range search module and a longitude and latitude large-range search module. In order to fill the longitude and latitude information of the standard address which lacks the longitude and latitude information in the standard address pool, the system further comprises an address clustering module, a cluster mean value calculation module and a missing filling module.
As shown in fig. 6, the target address to be matched and the standard address pool are filtered out by a longitude and latitude small-range search module, then the target address and the candidate standard address are input into a word segmentation module for processing, then a text similarity calculation module is input for calculating text similarity, then a text similarity judgment module is used for judging the text similarity and a preset threshold value, and when the maximum value of the text similarity is greater than or equal to the preset threshold value, the standard address with the maximum text similarity is used as the standard address for matching the target address. If the text similarity judgment is not in accordance with the condition, namely the maximum value of the text similarity is smaller than a preset threshold value, determining a larger range of candidate standard addresses in the target address to be matched and the standard address pool through a longitude and latitude large-range searching module, inputting the target address and the candidate standard address into a text similarity calculation module to calculate the text similarity, and finally judging the maximum value of the text similarity with the preset threshold value through a text similarity judgment module, wherein the steps can be repeated until the maximum value of the text similarity is larger than or equal to the preset threshold value, and then obtaining the standard address matched with the target address.
In order to fill the longitude and latitude information of the standard addresses with missing longitude and latitude information in the standard address pool, the standard addresses of the same class of clusters are obtained through the address clustering module, then the cluster mean value calculation module calculates the longitude and latitude average value of the standard addresses of the same class of clusters, and finally the longitude and latitude information is filled into the standard addresses with missing longitude and latitude information through the missing filling module.
It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.
Based on the same inventive concept, the embodiment of the application also provides an address matching device for realizing the address matching method. The implementation of the solution provided by the device is similar to the implementation described in the above method, so the specific limitation in the embodiments of one or more address matching devices provided below may be referred to the limitation of the address matching method hereinabove, and will not be repeated here.
In one embodiment, as shown in fig. 7, there is provided an address matching device 700 comprising: an acquisition module 701, a first calculation module 702 and a second calculation module 703, wherein:
the acquiring module 701 is configured to acquire a target address that needs to be address matched, and acquire a standard address pool, where the standard address pool includes a plurality of standard addresses;
the first calculating module 702 is configured to calculate a latitude and longitude difference between the target address and each standard address, and determine a plurality of candidate standard addresses from the standard address pool according to the calculated latitude and longitude difference;
the second calculating module 703 is configured to calculate a text similarity between the target address and each candidate standard address, and determine a standard address matching the target address from the plurality of candidate standard addresses according to the calculated text similarity.
In one embodiment, the method further includes a determining module, configured to determine latitude and longitude information of the first standard address according to a second standard address including latitude and longitude information in the standard address pool if the first standard address lacks the latitude and longitude information in the standard address pool.
In one embodiment, the determining module is specifically configured to calculate a text similarity between the first standard address and each second standard address, and determine a target standard address from the plurality of second standard addresses according to the calculated text similarity; and determining the same kind of standard addresses clustered into the same kind of cluster with the target standard addresses from the standard address pool, and determining the longitude and latitude information of the first standard address according to the longitude and latitude information of the same kind of standard addresses.
In one embodiment, the method further comprises a clustering module, which is used for clustering the plurality of second standard addresses according to the DBSCAN algorithm to obtain a plurality of class clusters.
In one embodiment, the determining module is specifically configured to determine the latitude and longitude information of the first standard address according to an average value of latitude and longitude information of the same class of standard addresses.
In one embodiment, the first calculating module 702 is specifically configured to calculate the euclidean distance between the target address and each standard address, and take the calculated euclidean distance as the longitude and latitude difference degree.
In one embodiment, the second calculating module 703 is configured to perform word segmentation on the target address and each candidate standard address, so as to generate a word vector of the target address and a word vector of each candidate standard address; and calculating cosine similarity of the word vector of the target address and the word vector of each candidate standard address, and taking the calculated cosine similarity as text similarity of the target address and each candidate standard address.
In one embodiment, the first calculating module 702 is specifically configured to use N standard addresses with minimum latitude and longitude differences as candidate standard addresses, where N is a positive integer.
In one embodiment, the second calculating module 703 is specifically configured to, if the maximum value of the text similarity is greater than or equal to a preset threshold, use the candidate standard address with the highest text similarity as the standard address matched with the target address; if the maximum value in the text similarity is smaller than a preset threshold value, M standard addresses with the smallest longitude and latitude difference degrees are used as candidate standard addresses, and the step of calculating the text similarity between the target address and each candidate standard address is carried out in a returning mode, wherein M is a positive integer larger than N.
The respective modules in the address matching device described above may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a terminal, and the internal structure thereof may be as shown in fig. 8. The computer device includes a processor, a memory, an input/output interface, a communication interface, a display unit, and an input means. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface, the display unit and the input device are connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless mode can be realized through WIFI, a mobile cellular network, NFC (near field communication) or other technologies. The computer program is executed by a processor to implement an address matching method. The display unit of the computer device is used for forming a visual picture, and can be a display screen, a projection device or a virtual reality imaging device. The display screen can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be a key, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.
It will be appreciated by those skilled in the art that the structure shown in FIG. 8 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In one embodiment, a computer device is provided comprising a memory and a processor, the memory having stored therein a computer program, the processor when executing the computer program performing the steps of: obtaining a target address which needs to be subjected to address matching, and obtaining a standard address pool, wherein the standard address pool comprises a plurality of standard addresses; calculating longitude and latitude difference degrees of the target address and each standard address, and determining a plurality of candidate standard addresses from a standard address pool according to the calculated longitude and latitude difference degrees; and calculating the text similarity between the target address and each candidate standard address, and determining the standard address matched with the target address from the plurality of candidate standard addresses according to the calculated text similarity.
In one embodiment, the processor when executing the computer program further performs the steps of: if a first standard address which lacks the longitude and latitude information exists in the standard address pool, determining the longitude and latitude information of the first standard address according to a second standard address which comprises the longitude and latitude information in the standard address pool.
In one embodiment, the processor when executing the computer program further performs the steps of: calculating the text similarity between the first standard address and each second standard address, and determining a target standard address from the plurality of second standard addresses according to the calculated text similarity; and determining the same kind of standard addresses clustered into the same kind of cluster with the target standard addresses from the standard address pool, and determining the longitude and latitude information of the first standard address according to the longitude and latitude information of the same kind of standard addresses.
In one embodiment, the processor when executing the computer program further performs the steps of: and clustering the second standard addresses according to the DBSCAN algorithm to obtain a plurality of class clusters.
In one embodiment, the processor when executing the computer program further performs the steps of: and determining the longitude and latitude information of the first standard address according to the average value of the longitude and latitude information of the same kind of standard addresses.
In one embodiment, the processor when executing the computer program further performs the steps of: and calculating the Euclidean distance between the target address and each standard address, and taking the Euclidean distance obtained by calculation as the longitude and latitude difference degree.
In one embodiment, the processor when executing the computer program further performs the steps of: word segmentation is carried out on the target address and each candidate standard address, and a word vector of the target address and a word vector of each candidate standard address are generated; and calculating cosine similarity of the word vector of the target address and the word vector of each candidate standard address, and taking the calculated cosine similarity as text similarity of the target address and each candidate standard address.
In one embodiment, the processor when executing the computer program further performs the steps of: and taking N standard addresses with the smallest longitude and latitude difference degree as candidate standard addresses, wherein N is a positive integer.
In one embodiment, the processor when executing the computer program further performs the steps of: if the maximum value in the text similarity is greater than or equal to a preset threshold value, the candidate standard address with the highest text similarity is used as the standard address matched with the target address; if the maximum value in the text similarity is smaller than a preset threshold value, M standard addresses with the smallest longitude and latitude difference degrees are used as candidate standard addresses, and the step of calculating the text similarity between the target address and each candidate standard address is carried out in a returning mode, wherein M is a positive integer larger than N.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of: obtaining a target address which needs to be subjected to address matching, and obtaining a standard address pool, wherein the standard address pool comprises a plurality of standard addresses; calculating longitude and latitude difference degrees of the target address and each standard address, and determining a plurality of candidate standard addresses from a standard address pool according to the calculated longitude and latitude difference degrees; and calculating the text similarity between the target address and each candidate standard address, and determining the standard address matched with the target address from the plurality of candidate standard addresses according to the calculated text similarity.
In one embodiment, the computer program when executed by the processor further performs the steps of: if a first standard address which lacks the longitude and latitude information exists in the standard address pool, determining the longitude and latitude information of the first standard address according to a second standard address which comprises the longitude and latitude information in the standard address pool.
In one embodiment, the computer program when executed by the processor further performs the steps of: calculating the text similarity between the first standard address and each second standard address, and determining a target standard address from the plurality of second standard addresses according to the calculated text similarity; and determining the same kind of standard addresses clustered into the same kind of cluster with the target standard addresses from the standard address pool, and determining the longitude and latitude information of the first standard address according to the longitude and latitude information of the same kind of standard addresses.
In one embodiment, the computer program when executed by the processor further performs the steps of: and clustering the second standard addresses according to the DBSCAN algorithm to obtain a plurality of class clusters.
In one embodiment, the computer program when executed by the processor further performs the steps of: and determining the longitude and latitude information of the first standard address according to the average value of the longitude and latitude information of the same kind of standard addresses.
In one embodiment, the computer program when executed by the processor further performs the steps of: and calculating the Euclidean distance between the target address and each standard address, and taking the Euclidean distance obtained by calculation as the longitude and latitude difference degree.
In one embodiment, the computer program when executed by the processor further performs the steps of: word segmentation is carried out on the target address and each candidate standard address, and a word vector of the target address and a word vector of each candidate standard address are generated; and calculating cosine similarity of the word vector of the target address and the word vector of each candidate standard address, and taking the calculated cosine similarity as text similarity of the target address and each candidate standard address.
In one embodiment, the computer program when executed by the processor further performs the steps of: and taking N standard addresses with the smallest longitude and latitude difference degree as candidate standard addresses, wherein N is a positive integer.
In one embodiment, the computer program when executed by the processor further performs the steps of: if the maximum value in the text similarity is greater than or equal to a preset threshold value, the candidate standard address with the highest text similarity is used as the standard address matched with the target address; if the maximum value in the text similarity is smaller than a preset threshold value, M standard addresses with the smallest longitude and latitude difference degrees are used as candidate standard addresses, and the step of calculating the text similarity between the target address and each candidate standard address is carried out in a returning mode, wherein M is a positive integer larger than N.
In one embodiment, a computer program product is provided comprising a computer program which, when executed by a processor, performs the steps of: obtaining a target address which needs to be subjected to address matching, and obtaining a standard address pool, wherein the standard address pool comprises a plurality of standard addresses; calculating longitude and latitude difference degrees of the target address and each standard address, and determining a plurality of candidate standard addresses from a standard address pool according to the calculated longitude and latitude difference degrees; and calculating the text similarity between the target address and each candidate standard address, and determining the standard address matched with the target address from the plurality of candidate standard addresses according to the calculated text similarity.
In one embodiment, the computer program when executed by the processor further performs the steps of: if a first standard address which lacks the longitude and latitude information exists in the standard address pool, determining the longitude and latitude information of the first standard address according to a second standard address which comprises the longitude and latitude information in the standard address pool.
In one embodiment, the computer program when executed by the processor further performs the steps of: calculating the text similarity between the first standard address and each second standard address, and determining a target standard address from the plurality of second standard addresses according to the calculated text similarity; and determining the same kind of standard addresses clustered into the same kind of cluster with the target standard addresses from the standard address pool, and determining the longitude and latitude information of the first standard address according to the longitude and latitude information of the same kind of standard addresses.
In one embodiment, the computer program when executed by the processor further performs the steps of: and clustering the second standard addresses according to the DBSCAN algorithm to obtain a plurality of class clusters.
In one embodiment, the computer program when executed by the processor further performs the steps of: and determining the longitude and latitude information of the first standard address according to the average value of the longitude and latitude information of the same kind of standard addresses.
In one embodiment, the computer program when executed by the processor further performs the steps of: and calculating the Euclidean distance between the target address and each standard address, and taking the Euclidean distance obtained by calculation as the longitude and latitude difference degree.
In one embodiment, the computer program when executed by the processor further performs the steps of: word segmentation is carried out on the target address and each candidate standard address, and a word vector of the target address and a word vector of each candidate standard address are generated; and calculating cosine similarity of the word vector of the target address and the word vector of each candidate standard address, and taking the calculated cosine similarity as text similarity of the target address and each candidate standard address.
In one embodiment, the computer program when executed by the processor further performs the steps of: and taking N standard addresses with the smallest longitude and latitude difference degree as candidate standard addresses, wherein N is a positive integer.
In one embodiment, the computer program when executed by the processor further performs the steps of: if the maximum value in the text similarity is greater than or equal to a preset threshold value, the candidate standard address with the highest text similarity is used as the standard address matched with the target address; if the maximum value in the text similarity is smaller than a preset threshold value, M standard addresses with the smallest longitude and latitude difference degrees are used as candidate standard addresses, and the step of calculating the text similarity between the target address and each candidate standard address is carried out in a returning mode, wherein M is a positive integer larger than N.
It should be noted that, the user information (including but not limited to user equipment information, user personal information, etc.) and the data (including but not limited to data for analysis, stored data, presented data, etc.) related to the present application are information and data authorized by the user or sufficiently authorized by each party, and the collection, use and processing of the related data need to comply with the related laws and regulations and standards of the related country and region.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the embodiments provided herein may include at least one of a relational database and a non-relational database. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processor referred to in the embodiments provided in the present application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, or the like, but is not limited thereto.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples illustrate only a few embodiments of the application and are described in detail herein without thereby limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of the application should be assessed as that of the appended claims.
Claims (13)
1. An address matching method, the method comprising:
obtaining a target address which needs to be subjected to address matching, and obtaining a standard address pool, wherein the standard address pool comprises a plurality of standard addresses;
calculating longitude and latitude difference degrees of the target address and each standard address, and determining a plurality of candidate standard addresses from the standard address pool according to the calculated longitude and latitude difference degrees;
And calculating the text similarity between the target address and each candidate standard address, and determining the standard address matched with the target address from the plurality of candidate standard addresses according to the calculated text similarity.
2. The method of claim 1, further comprising, prior to the obtaining the standard address pool:
if a first standard address which lacks the longitude and latitude information exists in the standard address pool, determining the longitude and latitude information of the first standard address according to a second standard address which comprises the longitude and latitude information in the standard address pool.
3. The method of claim 2, wherein determining the latitude and longitude information of the first standard address from a second standard address in the standard address pool that includes the latitude and longitude information comprises:
calculating the text similarity between the first standard address and each second standard address, and determining a target standard address from a plurality of second standard addresses according to the calculated text similarity;
and determining the same kind of standard addresses clustered into the same kind of clusters with the target standard addresses from the standard address pool, and determining the longitude and latitude information of the first standard address according to the longitude and latitude information of the same kind of standard addresses.
4. A method according to claim 3, wherein before determining from the pool of standard addresses a homogeneous standard address clustered into a same class cluster as the target standard address, the method further comprises:
and clustering the second standard addresses according to a DBSCAN algorithm to obtain a plurality of class clusters.
5. A method according to claim 3, wherein said determining the latitude and longitude information of the first standard address from the latitude and longitude information of the same class of standard addresses comprises:
and determining the longitude and latitude information of the first standard address according to the average value of the longitude and latitude information of the same kind of standard addresses.
6. The method according to any one of claims 1 to 5, wherein calculating the degree of latitude and longitude difference between the target address and each of the standard addresses includes:
and calculating the Euclidean distance between the target address and each standard address, and taking the Euclidean distance obtained by calculation as the longitude and latitude difference degree.
7. The method of claim 1, wherein said calculating the text similarity of the target address to each of the candidate standard addresses comprises:
word segmentation is carried out on the target address and each candidate standard address, and a word vector of the target address and a word vector of each candidate standard address are generated;
And calculating cosine similarity of the word vector of the target address and the word vector of each candidate standard address, and taking the calculated cosine similarity as text similarity of the target address and each candidate standard address.
8. The method of claim 1, wherein determining a plurality of candidate standard addresses from the standard address pool based on the calculated latitude and longitude differences comprises:
and taking N standard addresses with the smallest longitude and latitude difference as candidate standard addresses, wherein N is a positive integer.
9. The method of claim 8, wherein the determining a standard address from the plurality of candidate standard addresses that matches the target address based on the calculated text similarity comprises:
if the maximum value in the text similarity is greater than or equal to a preset threshold value, the candidate standard address with the highest text similarity is used as the standard address matched with the target address;
and if the maximum value in the text similarity is smaller than the preset threshold value, taking M standard addresses with the minimum longitude and latitude difference as candidate standard addresses, and returning to execute the step of calculating the text similarity between the target address and each candidate standard address, wherein M is a positive integer larger than N.
10. An address matching device, the device comprising:
the system comprises an acquisition module, a storage module and a storage module, wherein the acquisition module is used for acquiring a target address which needs to be subjected to address matching and acquiring a standard address pool, and the standard address pool comprises a plurality of standard addresses;
the first calculation module is used for calculating the longitude and latitude difference degrees of the target address and each standard address, and determining a plurality of candidate standard addresses from the standard address pool according to the calculated longitude and latitude difference degrees;
and the second calculation module is used for calculating the text similarity between the target address and each candidate standard address and determining the standard address matched with the target address from the plurality of candidate standard addresses according to the calculated text similarity.
11. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any one of claims 1 to 9 when the computer program is executed.
12. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 9.
13. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any one of claims 1 to 9.
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