Merchant name determination method, apparatus, device, medium, and product

Abstract

The application discloses a kind of merchant name determination method, device, equipment, medium and product, belong to internet technical field.The method comprises: in the case where target uniform resource locator url address and its corresponding target domain name are obtained, from domain name database, the first candidate domain name matched with target domain name and its corresponding first candidate merchant name are obtained;By accessing target url address, obtain web key information, obtain second candidate merchant name;The first keyword of target domain name is searched, and at least one third candidate merchant name matched with the first keyword is obtained;The candidate merchant list is sorted based on correlation weight and rationality weight, and the sorting result is output;Based on the sorting result, the target merchant name matched with the target url address in the candidate merchant name list is determined.According to the embodiment of the application, the merchant name information of the unaccepted merchant can be effectively obtained, and the coverage of offline accepted merchant is expanded.

Description

Technical Field

[0001] This application belongs to the field of Internet technology, and in particular relates to a method, apparatus, equipment, medium and product for determining a merchant name. Background Technology

[0002] With the development and application of internet technology, offline online payment has become an important payment method in users' daily lives. Users can make convenient payments by scanning merchants' QR codes.

[0003] In the context of the rapid promotion of online payment methods, payment platforms typically acquire information on merchants who haven't yet accepted payments through offline promotional methods during the market development process, and then establish acceptance partnerships. However, relying on manual methods is inefficient, resulting in numerous blind spots in offline acceptance. Therefore, how to obtain merchant name information for merchants who haven't yet accepted payments and eliminate these offline acceptance blind spots has become an urgent problem to be solved. Summary of the Invention

[0004] This application provides a method, apparatus, device, medium, and product for determining merchant names, which can effectively obtain merchant name information of merchants who have not accepted applications, thereby expanding the coverage of offline accepting merchants.

[0005] In a first aspect, embodiments of this application provide a method for determining a merchant name, the method comprising:

[0006] Once the target Uniform Resource Locator (URL) address and its corresponding target domain name are obtained, the first candidate domain name matching the target domain name and its corresponding first candidate merchant name are retrieved from the domain name database. The target URL address is the URL obtained by the client scanning the QR code of the unaccepted merchant.

[0007] By accessing the target URL, key information on the webpage is obtained, leading to the second candidate merchant name.

[0008] Search for the first keyword of the target domain name to obtain at least one third candidate merchant name that matches the first keyword;

[0009] The candidate merchant list is sorted based on relevance weight and rationality weight, and the sorting result is output. The candidate merchant list includes the first candidate merchant name, the second candidate merchant name, and at least one third candidate merchant name.

[0010] Based on the sorting results, the target merchant name that matches the target URL address is determined from the list of candidate merchant names.

[0011] Secondly, embodiments of this application provide a merchant name determination device, the device comprising:

[0012] The acquisition module is used to obtain the first candidate domain name and its corresponding first candidate merchant name that match the target domain name from the domain name database when the target Uniform Resource Locator URL address and its corresponding target domain name are obtained. The target URL address is the URL obtained by the client scanning the QR code of the unaccepted merchant.

[0013] The acquisition module is also used to obtain key information of the webpage by accessing the target URL address, and to obtain the second candidate merchant name;

[0014] The retrieval module is used to retrieve the first keyword of the target domain name and obtain at least one third candidate merchant name that matches the first keyword;

[0015] The output module is used to sort the candidate merchant list based on relevance weight and rationality weight, and output the sorting result. The candidate merchant list includes the first candidate merchant name, the second candidate merchant name, and at least one third candidate merchant name.

[0016] The determination module is used to determine the target merchant name that matches the target URL address in the candidate merchant name list based on the sorting results.

[0017] Thirdly, embodiments of this application provide an electronic device, including: a processor and a memory storing computer program instructions; the processor executes the computer program instructions to implement the steps of the merchant name determination method shown in the first aspect.

[0018] Fourthly, embodiments of this application provide a computer-readable storage medium storing a program or instructions, which, when executed by a processor, implement the steps of the merchant name determination method as described in the first aspect.

[0019] Fifthly, embodiments of this application provide a computer program product stored in a non-volatile storage medium, which, when executed by at least one processor, implements the steps of the merchant name determination method as described in the first aspect.

[0020] In a sixth aspect, embodiments of this application provide a chip including a processor and a communication interface, the communication interface being coupled to the processor, the processor being used to run programs or instructions to implement the steps of the merchant name determination method as described in the first aspect.

[0021] This application provides a method, apparatus, device, medium, and product for determining merchant names. For merchants not accepted offline, the client will obtain an incorrect URL when scanning the merchant's QR code. Therefore, the payment platform can obtain the incorrect URL (i.e., the target URL address) and its corresponding target domain name from the domain name database, retrieving a first candidate domain name matching the target domain name and its corresponding first candidate merchant name. Furthermore, by accessing the target URL address, key information can be obtained from the accessed webpage to obtain a second candidate merchant name matching the target URL address. In the retrieval step, since "url-merchant name" differs from "search term-search result" in traditional retrieval tasks, it is difficult to retrieve merchant name results using the target URL address. Therefore, it is necessary to extract keywords from the target domain name corresponding to the target URL address to obtain a first keyword, and then search for this first keyword to obtain at least one third candidate merchant name matching the first keyword. Based on this, after obtaining candidate merchant names through the above three acquisition methods, this application uses relevance weight and reasonableness weight to jointly determine and provide a ranking result of all candidate merchant names. Based on the ranking result, the target merchant name matching the target URL address is selected from all candidate merchant names, thereby accurately and effectively obtaining the merchant name information of unaccepted merchants. Based on this merchant name information, the payment platform can carry out acceptance business for unaccepted merchants, which can effectively expand the coverage of offline acceptance merchants. Attached Figure Description

[0022] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 A flowchart of an embodiment of the merchant name determination method provided in the first aspect of this application;

[0024] Figure 2 A flowchart of another embodiment of the merchant name determination method provided in the first aspect of this application;

[0025] Figure 3 A flowchart of yet another embodiment of the merchant name determination method provided in the first aspect of this application;

[0026] Figure 4 A flowchart of yet another embodiment of the merchant name determination method provided in the first aspect of this application;

[0027] Figure 5 A flowchart of yet another embodiment of the merchant name determination method provided in the first aspect of this application;

[0028] Figure 6 A schematic diagram of the structure of an embodiment of the merchant name determination device provided in the second aspect of this application;

[0029] Figure 7 A schematic diagram of the structure of an embodiment of the electronic device provided in the third aspect of this application. Detailed Implementation

[0030] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0031] With the development and application of internet technology, offline online payment has become an important payment method in users' daily lives, allowing them to conveniently pay by scanning merchants' QR codes. Against the backdrop of the rapid promotion of online payment methods, payment platforms typically acquire information on merchants who haven't yet accepted payment services through offline promotional methods during the market development process, and then subsequently establish acceptance partnerships. However, relying on manual methods is inefficient, resulting in numerous blind spots in offline acceptance. Therefore, how to obtain merchant information for those who haven't yet accepted payment services and eliminate these offline acceptance blind spots has become an urgent problem to be solved.

[0032] To address the aforementioned issues, this application provides a merchant name determination method, apparatus, device, medium, and product. This method can obtain the erroneous URL acquired by the client when scanning the QR code of an unaccepted merchant, and obtain the target domain name corresponding to the erroneous URL (i.e., the target URL address). Based on the target URL address and the target domain name, candidate merchant names can be obtained through three acquisition methods. Furthermore, this application sorts all candidate merchant names based on relevance and reasonableness weights, and selects the target merchant name matching the target URL address from all candidate merchant names based on the sorting results. This effectively obtains the merchant name information of unaccepted merchants. Based on this merchant name information, the payment platform can conduct acceptance business for unaccepted merchants, effectively expanding the coverage of offline accepting merchants.

[0033] The merchant name determination method in this application embodiment can be applied to information acquisition scenarios for obtaining merchant name information of offline merchants who have not accepted business. The merchant name determination method provided in this application embodiment will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0034] The first aspect of this application provides a method for determining a merchant name, which can be applied to electronic devices, meaning that the method for determining a merchant name can be executed by an electronic device. It should be noted that the aforementioned executing entity does not constitute a limitation on this application.

[0035] For example, the electronic device could be a server on the payment platform side.

[0036] Figure 1 A flowchart illustrating an embodiment of the merchant name determination method provided in the first aspect of this application. Figure 1 As shown, the method for determining the merchant name may include steps 110-150.

[0037] Step 110: After obtaining the target Uniform Resource Locator (URL) address and its corresponding target domain name, retrieve the first candidate domain name that matches the target domain name and its corresponding first candidate merchant name from the domain name database.

[0038] The target URL is the URL obtained by the client when scanning the QR code of a merchant that has not accepted the service.

[0039] Step 120: Obtain key information from the webpage by accessing the target URL address to get the second candidate merchant name.

[0040] Step 130: Search for the first keyword of the target domain name to obtain at least one third candidate merchant name that matches the first keyword.

[0041] Step 140: Sort the candidate merchant list based on relevance weight and rationality weight, and output the sorting result. The candidate merchant list includes the first candidate merchant name, the second candidate merchant name, and at least one third candidate merchant name.

[0042] Step 150: Based on the sorting results, determine the target merchant name in the candidate merchant name list that matches the target URL address.

[0043] The merchant name determination method provided in this application embodiment addresses the issue that for merchants not accepting offline services, the client will obtain an incorrect URL when scanning the QR code of such a merchant. Therefore, the payment platform can retrieve a first candidate domain name matching the target domain name and its corresponding first candidate merchant name from the domain name database upon obtaining the incorrect URL (i.e., the target URL address) and its corresponding target domain name. Furthermore, by accessing the target URL address, key information about the webpage can be obtained, leading to a second candidate merchant name matching the target URL address. In the retrieval step, since "url-merchant name" differs from "search term-search result" in traditional retrieval tasks, it is difficult to find merchant name results using the target URL address alone. Therefore, it is necessary to extract keywords from the target domain name corresponding to the target URL address to obtain a first keyword, and then search for this first keyword to obtain at least one third candidate merchant name matching the first keyword. Based on this, after obtaining candidate merchant names through the above three acquisition methods, this application uses relevance weight and reasonableness weight to jointly determine and provide a ranking result of all candidate merchant names. Based on the ranking result, the target merchant name matching the target URL address is selected from all candidate merchant names, thereby accurately and effectively obtaining the merchant name information of unaccepted merchants. Based on this merchant name information, the payment platform can carry out acceptance business for unaccepted merchants, which can effectively expand the coverage of offline acceptance merchants.

[0044] The specific implementation of the above steps will be described in detail below with reference to the embodiments.

[0045] In step 110, a Uniform Resource Locator (URL) is a concise representation of the location and access method of a resource that can be obtained from the Internet; it is the address of a standard resource on the Internet. The target URL is the erroneous URL obtained by the client when scanning a QR code from a merchant that does not accept payment requests. This QR code can be a payment code. The target domain name is the domain name corresponding to the target URL.

[0046] After obtaining the error URL, the client can record the error URL in the log data and report the log data to the payment platform.

[0047] Before step 110, the method may further include: the electronic device acquiring log data reported by the client, and using a log filtering tool to filter the log data reported by the client to obtain the target URL address.

[0048] In some embodiments of this application, the domain name database may include multiple domain names and their corresponding merchant names. To obtain the first candidate merchant name matching the target URL address from the domain name database, Figure 2 A flowchart of another embodiment of the merchant name determination method provided in the first aspect of this application, step 110 may specifically include: Figure 2 Steps 210 and 220 are shown.

[0049] Step 210: Calculate the similarity between the target domain name and each domain name based on the text similarity matching algorithm.

[0050] The domain name database is a knowledge accumulation formed during the initial manual processing, and its main content is the merchant name and its corresponding domain name address.

[0051] For example, the text similarity matching algorithm can be the Jaccard similarity algorithm, the Levenshtein distance algorithm, the Best Matching (BM) algorithm, etc., and this application does not specifically limit it.

[0052] Taking the Levenshtein distance algorithm as an example for text similarity matching, the Levenshtein distance, also known as edit distance, refers to the minimum number of editing operations required to transform one string into another. These editing operations can include character substitution, character insertion, and character deletion. The similarity between two strings is negatively correlated with the Levenshtein distance; that is, the longer the Levenshtein distance, the lower the similarity, and the shorter the Levenshtein distance, the higher the similarity.

[0053] For example, if the target domain name is 'a', and the domain name 'b' is in the domain name database, then the Levenshtein distance between 'a' and 'b' can be calculated using formula (1). a，b (|a|,|b|), the similarity between a and b is calculated using formula (2). a , b :

[0054]

[0055]

[0056] Where |a| and |b| represent the string lengths of target domain name a and domain name b, respectively. i =b i hour, Otherwise, it is 1, lev a，b (i, j) represents the edit distance between the first i characters of a and the first j characters of b.

[0057] Step 220: Determine the domain name with the highest similarity to the target domain name as the first candidate domain name, and the merchant name corresponding to the first candidate domain name is the first candidate merchant name.

[0058] In this embodiment, considering that it is not possible to directly use the target URL address to find the merchant name, this application first obtains the target domain name corresponding to the target URL address, and uses a text similarity matching algorithm to accurately calculate the similarity between the target domain name and the domain name in the domain name database. In this way, the first candidate domain name with a high similarity can be found with the help of the target domain name. By obtaining the merchant name corresponding to the first candidate domain name, the first candidate merchant name with a high matching degree with the target domain name and the target URL address can be obtained. This method of obtaining the merchant name is relatively accurate, the steps are simple, and the efficiency is high.

[0059] In step 120, the key information of the webpage can be the webpage title, webpage copyright, etc. The second candidate merchant name is obtained based on the key information of the webpage. For example, the second candidate merchant name can be the key information of the webpage. Since the second candidate merchant name is a webpage element obtained by accessing the target URL address, the second candidate merchant name matches the target URL address.

[0060] Traditional methods of accessing URLs typically use web crawling techniques, which frequently encounter anti-crawling mechanisms such as header restrictions, login verification, protocol / IP address restrictions, and dynamic loading, impacting processing efficiency. To address this issue, this application constructs an improved browser-driven crawler to achieve automated browser control.

[0061] In some embodiments of this application, Figure 3 A flowchart of yet another embodiment of the merchant name determination method provided in the first aspect of this application is shown below. Figure 3 As shown, after step 110 and before step 120, the method may also include steps 310-330.

[0062] Step 310: Obtain the currently running browser process based on the browser's installation path parameter.

[0063] Step 320: Obtain the remote debugging port information of the browser process.

[0064] Step 330: Launch the browser by executing the target command to drive chromedriver.

[0065] The target command includes remote debugging port information, which can be a port number. This remote debugging port is the port of the currently running browser process. By providing this port number to chromedriver, you can connect to the currently running browser process to perform subsequent automated control operations such as opening the browser, creating new tabs, accessing web pages, extracting web page elements, inputting characters, clicking buttons, and closing tabs.

[0066] In this embodiment, the electronic device can block the creation of a new browser process by chromedriver based on the remote debugging port information of the currently running browser process. It can start the browser instance by executing the target command, which facilitates subsequent automated control operations, builds a driver-driven crawler and improves the browser's native interface, thereby optimizing the browser-driven crawler.

[0067] In some embodiments of this application, after launching the browser based on step 330 above, step 120 may specifically include the following steps: accessing the target URL address through the browser, obtaining the webpage title and webpage copyright, and obtaining key information of the webpage; determining the key information of the webpage as the second candidate merchant name.

[0068] It should be noted that, apart from the webpage title and webpage copyright, the key information of the webpage can also be key elements displayed on other webpages, and this application does not impose specific restrictions on this.

[0069] In this embodiment, after blocking the creation of new browser processes by chromedriver, the target URL can be accessed based on the currently running browser process, avoiding the frequent closing and re-opening of the browser each time the URL is accessed, thus improving operating efficiency.

[0070] In step 130, the first keyword is a keyword extracted from the target domain name, and the third candidate merchant name is a merchant name that matches the first keyword.

[0071] For example, if the target domain name is wpay.sdXXXcu.com, then sdXXXcu is the first keyword extracted from the target domain name.

[0072] In some embodiments of this application, after launching the browser based on step 330 above, step 130 may specifically include: accessing a search engine through the browser and retrieving the first keyword in the search engine.

[0073] In this embodiment of the application, the electronic device is limited to opening the search engine through the previously launched browser in the retrieval step. This allows the browser to be accessed by manual physical operation first, and then chromedriver is used to take over the retrieval operation of the current browser process, maintaining the stability and continuity of the crawler access and avoiding anti-crawling restrictions.

[0074] In some embodiments of this application, Figure 4 A flowchart of another embodiment of the merchant name determination method provided in the first aspect of this application, step 130 may specifically include... Figure 4 Steps 410-430 are shown.

[0075] Step 410: Search for the first keyword in the search engine and obtain at least one search result.

[0076] The search results are those retrieved by the search engine based on the relevance of the first keyword after the first keyword is entered into the search engine.

[0077] Step 420: Based on the keyword extraction algorithm, extract the second keyword from all search results.

[0078] Keyword extraction algorithms can be based on statistical features, word graph models, or topic models.

[0079] In one embodiment, step 420 may specifically include: determining the importance score corresponding to each keyword in the search results based on the keyword extraction algorithm, wherein the importance score is used to characterize the importance of the keyword in the search results; and determining the keywords with an importance score greater than a preset importance threshold as the second keywords.

[0080] Taking the TF-IDF algorithm as an example for keyword extraction, TF-IDF is used to evaluate the importance of a word to a document within a document set or corpus. The importance of a word increases proportionally to the number of times it appears in the document and decreases inversely proportionally to its frequency in the corpus. Therefore, the importance score can be positively correlated with the frequency of the keyword in the corresponding search results and negatively correlated with the frequency of the keyword in the corpus, which includes at least one of the aforementioned search results.

[0081] Step 430: Determine at least one second keyword in the search results as the third candidate merchant name.

[0082] In this embodiment of the application, the search results retrieved in the search engine are usually documents, articles, etc. Based on this, in order to obtain merchant name information that matches the target URL address, the electronic device extracts the second keyword from each search result based on the keyword extraction algorithm. Since the second keyword has a high degree of matching with the first keyword, the second keyword is used as the merchant name information that matches the target domain name and the target URL address, and the accuracy is high.

[0083] It should be noted that this application does not specifically limit the execution order of steps 110 to 130 above. Step 120 can be performed before or after step 110, and step 130 can be performed before or after step 120.

[0084] In step 140, the candidate merchant list includes N candidate merchant names, which include a first candidate merchant name, a second candidate merchant name, and at least one third candidate merchant name.

[0085] Among them, the first candidate merchant name, the second candidate merchant name, and at least one third candidate merchant name all have corresponding rationality weights. These rationality weights are negatively correlated with the first relevance, which can be seen as the degree of association between the candidate merchant name and invalid information. In other words, the rationality weights can be used to characterize the degree of association between the candidate merchant name and valid information. At least one third candidate merchant name also has a corresponding relevance weight, which is used to characterize the degree of relevance between the third candidate merchant name and the first keyword.

[0086] In some embodiments of this application, in order to reasonably allocate relevance weights and rationality weights and improve the accuracy of the ranking results, Figure 5 A flowchart of another embodiment of the merchant name determination method provided in the first aspect of this application, step 140 may specifically include: Figure 5 Steps 510-550 are shown.

[0087] Step 510: Assign corresponding rationality weights to the N candidate merchant names using a preset classification model.

[0088] Specifically, a first degree of correlation between each candidate merchant name and invalid information is determined based on a preset classification model, and a reasonableness weight is determined based on the first degree of correlation. The reasonableness weight is negatively correlated with the first degree of correlation.

[0089] The aforementioned invalid information can be, for example, information unrelated to the merchant's name such as "Please wait," "Login," "Cashier," or "Aggregator Code Prompt." Correspondingly, valid information is information closely related to the merchant's name.

[0090] The preset classification model can be set according to specific needs. For example, it can be a machine learning model such as Support Vector Machine (SVM) or Logistic Regression (LR), or a neural network model such as Recurrent Neural Network (RNN) or Long Short-Term Memory (LSTM). This application does not make any specific restrictions on this.

[0091] Step 520: Assign a corresponding relevance weight to at least one third candidate merchant name.

[0092] Among them, the relevance weight is used to characterize the degree of relevance between the third candidate merchant name and the first keyword.

[0093] Step 530: Use the reasonableness weight as the matching score for the first candidate merchant name and the second candidate merchant name.

[0094] In one example, the first candidate merchant is named A, and the reasonableness weight corresponding to the first candidate merchant is α1. The second candidate merchant is named B, and the reasonableness weight corresponding to the second candidate merchant is α2. Then the matching score of A can be α1, and the matching score of B can be α2.

[0095] Step 540: The sum of the first score and the second score is used as the matching score for the third candidate merchant name.

[0096] The first score is the product of the rationality weight and the first coefficient, the second score is the product of the relevance weight and the second coefficient, and the sum of the first and second coefficients is 1. The first and second coefficients can be set according to specific needs, and this application does not impose specific limitations on them.

[0097] It should be noted that the first and second coefficients corresponding to different third candidate merchant names may be the same or different, and this application does not impose specific restrictions on this.

[0098] In one example, the third candidate merchant names include C1 and C2. The reasonableness weight and relevance weight of C1 are α3 and β1, respectively, and the reasonableness weight and relevance weight of C2 are α4 and β2, respectively. The first coefficient is 0.6 and the second coefficient is 0.4. Then the matching score of C1 is α3*0.6+β1*0.4, and the matching score of C2 is α4*0.6+β2*0.4.

[0099] Step 550: Output N candidate merchant names in descending order of matching score, or output the top M candidate merchant names.

[0100] Where M and N are both positive integers, M can be set according to specific needs, such as M being a preset quantity, or M being determined based on N, such as M being 1 / 2 or 1 / 3 of N, etc.

[0101] In this embodiment, candidate merchant names may contain invalid information unrelated to the merchant name. Therefore, to filter out such candidate merchant names, this application assigns a corresponding reasonableness weight to each candidate merchant name. This reasonableness weight is inversely proportional to the first correlation between the candidate merchant name and the invalid information. Therefore, this reasonableness weight is used to determine the matching score. The matching score reflects the correlation between the candidate merchant name and the valid merchant name, or it can characterize the probability that the candidate merchant name is a valid merchant name, thus improving the accuracy of the matching score. A relevance weight is used to characterize the relevance between the third candidate merchant name and the first keyword, which is the keyword of the target domain name corresponding to the target URL address. Therefore, this relevance weight is used to determine the matching score. The matching score can accurately measure the relevance between the third candidate merchant name and the target domain name and the target URL address, further improving the accuracy of the matching score. Based on this, through the joint determination of the above relevance weight and reasonableness weight, all candidate merchant names can be reasonably sorted to obtain an accurate sorting result, thereby ensuring that the most reasonable and matching merchant name is output to the target URL address based on this sorting result.

[0102] In this embodiment of the application, in order to determine the relevance weight of each third candidate merchant name, the method may further include the following steps: constructing a corpus based on at least one search result; calculating the importance score of each second keyword based on a keyword extraction algorithm, wherein the importance score is positively correlated with the frequency of occurrence of the second keyword in the corresponding search result and negatively correlated with the frequency of occurrence of the second keyword in the corpus; and determining the relevance weight of the third candidate merchant name corresponding to the second keyword based on the importance score of the second keyword, wherein the relevance weight is positively correlated with the importance score.

[0103] In step 150, based on the ranking results, the electronic device can determine that the candidate merchant with the highest matching score is the target merchant name, or receive a first input from the user regarding the ranking results, and in response to the first input, determine that the input object of the first input is the target merchant name.

[0104] The first input can be the user's selection of a candidate merchant name from the sorting results.

[0105] Based on the same inventive concept, the second aspect of this application provides a merchant name determination device. Figure 6 A schematic diagram of an embodiment of the merchant name determination device provided in the second aspect of this application.

[0106] like Figure 6 As shown, the merchant name determination device 600 may specifically include: an acquisition module 610, a retrieval module 620, an output module 630, and a determination module 640.

[0107] The acquisition module 610 is used to obtain, in the case of obtaining the target Uniform Resource Locator URL address and its corresponding target domain name, the first candidate domain name matching the target domain name and its corresponding first candidate merchant name from the domain name database. The target URL address is the URL obtained by the client scanning the QR code of the unaccepted merchant.

[0108] The acquisition module 610 is also used to obtain key information of the webpage by accessing the target URL address and to obtain the second candidate merchant name;

[0109] The retrieval module 620 is used to retrieve the first keyword of the target domain name and obtain at least one third candidate merchant name that matches the first keyword;

[0110] The output module 630 is used to sort the candidate merchant list based on relevance weight and rationality weight, and output the sorting result. The candidate merchant list includes the first candidate merchant name, the second candidate merchant name and at least one third candidate merchant name.

[0111] The determination module 640 is used to determine the target merchant name that matches the target URL address in the candidate merchant name list based on the sorting results.

[0112] The merchant name determination device provided in this application embodiment, for merchants that are not accepted offline, will obtain an incorrect URL when the client scans the QR code of the merchant. Therefore, the payment platform can obtain the first candidate domain name and its corresponding first candidate merchant name matching the target domain name from the domain name database after obtaining the incorrect URL (i.e., the target URL address) and its corresponding target domain name. Furthermore, by accessing the target URL address, key information of the webpage can be obtained from the accessed webpage to obtain a second candidate merchant name matching the target URL address. In the retrieval step, since "url-merchant name" is different from "search term-search result" in traditional retrieval tasks, it is difficult to retrieve merchant name results using the target URL address. Therefore, it is necessary to extract keywords from the target domain name corresponding to the target URL address to obtain the first keyword, and then search for the first keyword to obtain at least one third candidate merchant name matching the first keyword. Based on this, after obtaining candidate merchant names through the above three acquisition methods, this application uses relevance weight and reasonableness weight to jointly determine and provide a ranking result of all candidate merchant names. Based on the ranking result, the target merchant name matching the target URL address is selected from all candidate merchant names, thereby accurately and effectively obtaining the merchant name information of unaccepted merchants. Based on this merchant name information, the payment platform can carry out acceptance business for unaccepted merchants, which can effectively expand the coverage of offline acceptance merchants.

[0113] In some embodiments of this application, the domain name database includes multiple domain names and their corresponding merchant names. The acquisition module 610 includes: a calculation unit, used to calculate the similarity between the target domain name and each domain name based on a text similarity matching algorithm; and a determination unit, used to determine the domain name with the highest similarity to the target domain name as the first candidate domain name, and the merchant name corresponding to the first candidate domain name as the first candidate merchant name.

[0114] In some embodiments of this application, the apparatus further includes: an acquisition module 610, which is further configured to acquire the currently running browser process based on the browser's installation path parameters after acquiring the first candidate domain name matching the target domain name and its corresponding first candidate merchant name from the domain name database; the acquisition module 610 is further configured to acquire the remote debugging port information of the browser process; and a startup module, which is configured to start the browser by executing a target command to drive chromedriver, wherein the target command includes the remote debugging port information.

[0115] In some embodiments of this application: the acquisition module 610 is specifically used to: access the target URL address through a browser, obtain the webpage title and webpage copyright, and obtain the key information of the webpage; determine the key information of the webpage as the second candidate merchant name; the retrieval module 620 is specifically used to: access the search engine through a browser and retrieve the first keyword in the search engine.

[0116] In some embodiments of this application, the candidate merchant list includes N candidate merchant names, which include a first candidate merchant name, a second candidate merchant name, and at least one third candidate merchant name. The output module 630 specifically includes: an allocation unit, configured to assign corresponding rationality weights to the N candidate merchant names using a preset classification model, wherein the rationality weights are negatively correlated with a first correlation degree, which is the degree of association between the candidate merchant name and invalid information; and an allocation unit further configured to assign corresponding relevance weights to at least one third candidate merchant name, wherein the relevance weights are used for... The system represents the relevance of the third candidate merchant name to the first keyword; the scoring unit is used to determine the relevance score of the first and second candidate merchant names based on the reasonableness weight; the scoring unit is also used to determine the relevance score of the third candidate merchant name by summing the first score and the second score, where the first score is the product of the reasonableness weight and the first coefficient, and the second score is the product of the relevance weight and the second coefficient; the output unit is used to output N candidate merchant names in descending order of relevance score, or to output the top M candidate merchant names.

[0117] In some embodiments of this application, the retrieval module 620 includes: a retrieval unit for retrieving a first keyword in a search engine to obtain at least one retrieval result; an extraction unit for extracting a second keyword from all retrieval results based on a keyword extraction algorithm; and a determination unit for determining that the second keyword in at least one retrieval result is a third candidate merchant name.

[0118] In some embodiments of this application, the apparatus further includes: a construction module for constructing a corpus based on at least one search result; a calculation module for calculating the importance score of each second keyword based on a keyword extraction algorithm, wherein the importance score is positively correlated with the number of times the second keyword appears in the corresponding search result and negatively correlated with the frequency of the second keyword in the corpus; and a determination unit for determining the relevance weight of the third candidate merchant name corresponding to the second keyword based on the importance score of the second keyword, wherein the relevance weight is positively correlated with the importance score.

[0119] In some embodiments of this application, the determining module 640 is specifically used to: determine the candidate merchant name with the highest matching score as the target merchant name.

[0120] In some embodiments of this application, the apparatus further includes: a filtering module, used to filter the log data reported by the client using a log filtering tool to obtain the target URL address before obtaining the first candidate domain name matching the target domain name and its corresponding first candidate merchant name from the domain name database.

[0121] A third aspect of this application also provides an electronic device. Figure 7 A schematic diagram of the structure of an embodiment of the electronic device provided in the third aspect of this application. (See attached diagram.) Figure 7 As shown, the electronic device 700 includes a memory 701, a processor 702, and a computer program stored in the memory 701 and executable on the processor 702.

[0122] In one example, the processor 702 described above may include a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0123] Memory 701 may include read-only memory (ROM), random access memory (RAM), disk storage media device, optical storage media device, flash memory device, electrical, optical, or other physical / tangible memory storage device. Therefore, typically, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the merchant name determination method in the embodiments according to the first aspect of this application.

[0124] The processor 702 runs a computer program corresponding to the executable program code by reading the executable program code stored in the memory 701, in order to implement the merchant name determination method in the embodiment of the first aspect above.

[0125] In some examples, the electronic device 700 may also include a communication interface 703 and a bus 704. For example, Figure 7 As shown, the memory 701, processor 702, and communication interface 703 are connected through bus 704 and complete communication with each other.

[0126] The communication interface 703 is mainly used to enable communication between various modules, devices, units, and / or equipment in the embodiments of this application. Input devices and / or output devices can also be connected through the communication interface 703.

[0127] Bus 704 includes hardware, software, or both, that couples components of electronic device 700 together. For example, and not as a limitation, bus 704 may include an Accelerated Graphics Port (AGP) or other graphics bus, an Enhanced Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Micro Channel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-E) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local Bus (VLB) bus, or other suitable buses, or a combination of two or more of these. Where appropriate, bus 704 may include one or more buses. Although specific buses are described and illustrated in the embodiments of this application, this application considers any suitable bus or interconnection.

[0128] A fourth aspect of this application provides a computer-readable storage medium storing a program or instructions. When executed by a processor, the program or instructions can implement the merchant name determination method described in the first aspect and achieve the same technical effect. To avoid repetition, further details are omitted here. The aforementioned computer-readable storage medium may include non-transitory computer-readable storage media, such as read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks, etc., and is not limited thereto.

[0129] The fifth aspect of this application provides a computer program product stored in a non-volatile storage medium. When executed by at least one processor, the computer program product implements the steps of the merchant name determination method as shown in the first aspect. The specific content of the merchant name determination method can be found in the relevant descriptions in the above embodiments, and will not be repeated here.

[0130] The sixth aspect of this application provides a chip including a processor and a communication interface, the communication interface and the processor being coupled together. The processor is used to run programs or instructions to implement various processes of the merchant name determination method embodiment as shown in the first aspect, and can achieve the same technical effect. To avoid repetition, it will not be described again here.

[0131] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0132] It should be clarified that the various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. For the device embodiments, user terminal embodiments, equipment embodiments, system embodiments, and computer-readable storage medium embodiments, the relevant parts can be referred to the description section of the method embodiments. This application is not limited to the specific steps and structures described above and shown in the figures. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application. Furthermore, for the sake of brevity, detailed descriptions of known methods and techniques are omitted here.

[0133] The aspects of this application have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by dedicated hardware performing the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0134] Those skilled in the art will understand that the above embodiments are exemplary and not restrictive. Different technical features appearing in different embodiments can be combined to achieve beneficial effects. Based on a study of the drawings, specification, and claims, those skilled in the art should be able to understand and implement other variations of the disclosed embodiments. In the claims, the term "comprising" does not exclude other means or steps; the quantifier "a" does not exclude a plurality; the terms "first" and "second" are used to identify names and not to indicate any particular order. No reference numerals in the claims should be construed as limiting the scope of protection. The functionality of multiple parts appearing in the claims can be implemented by a single hardware or software module. The appearance of certain technical features in different dependent claims does not mean that these technical features cannot be combined to achieve beneficial effects.

Claims

1. A method for determining a merchant name, characterized in that, The method includes: If the target Uniform Resource Locator (URL) address and its corresponding target domain name are obtained, the first candidate domain name matching the target domain name and its corresponding first candidate merchant name are obtained from the domain name database. The target URL address is the URL obtained by the client scanning the QR code of the unaccepted merchant. Based on the browser's installation path parameter, obtain the currently running browser process; Obtain the remote debugging port information of the browser process, wherein the remote debugging port information is the port number; The browser is launched by executing a target command that drives chromedriver, and the target command includes the remote debugging port information; By accessing the target URL address through the browser, the webpage title and copyright information can be obtained, thus acquiring key information about the webpage. The key information on the webpage was determined to be the second candidate merchant name; Access the search engine through the browser and search for the first keyword of the target domain name in the search engine to obtain at least one third candidate merchant name that matches the first keyword; The candidate merchant list is sorted based on relevance weight and rationality weight, and the sorting result is output. The candidate merchant list includes the first candidate merchant name, the second candidate merchant name, and the at least one third candidate merchant name. Based on the sorting results, the target merchant name that matches the target URL address is determined from the candidate merchant name list.

2. The method according to claim 1, characterized in that, The domain name database includes multiple domain names and their corresponding merchant names. The step of retrieving a first candidate domain name matching the target domain name from the domain name database and its corresponding first candidate merchant name includes: Based on a text similarity matching algorithm, the similarity between the target domain name and each of the domain names is calculated; The domain name with the highest similarity to the target domain name is determined as the first candidate domain name, and the merchant name corresponding to the first candidate domain name is the first candidate merchant name.

3. The method according to claim 1, characterized in that, The candidate merchant list includes N candidate merchant names, which include the first candidate merchant name, the second candidate merchant name, and at least one third candidate merchant name. The candidate merchant list is sorted based on relevance weight and reasonableness weight, and the sorting result is output, including: A pre-defined classification model is used to assign corresponding rationality weights to the N candidate merchant names. The rationality weights are negatively correlated with a first correlation degree, which is the degree of association between the candidate merchant name and invalid information. Assign a corresponding relevance weight to the at least one third candidate merchant name, the relevance weight being used to characterize the degree of relevance between the third candidate merchant name and the first keyword; The reasonableness weight is used as the matching score between the first candidate merchant name and the second candidate merchant name; The sum of the first score and the second score is used as the matching score of the third candidate merchant name, wherein the first score is the product of the rationality weight and the first coefficient, and the second score is the product of the relevance weight and the second coefficient. Output the N candidate merchant names in descending order of matching scores, or output the top M candidate merchant names.

4. The method according to claim 1 or 3, characterized in that, The step of accessing a search engine through the browser and retrieving the first keyword of the target domain name in the search engine to obtain at least one third candidate merchant name matching the first keyword includes: Searching for the first keyword in a search engine yields at least one search result; Based on the keyword extraction algorithm, the second keyword is extracted from all the search results; The second keyword in the at least one search result is determined as the third candidate merchant name.

5. The method according to claim 4, characterized in that, The method further includes: A corpus is constructed based on at least one of the search results; Based on the keyword extraction algorithm, the importance score of each second keyword is calculated, wherein the importance score is positively correlated with the number of times the second keyword appears in the corresponding search results and negatively correlated with the frequency of the second keyword in the corpus. Based on the importance score of the second keyword, the relevance weight of the third candidate merchant name corresponding to the second keyword is determined, and the relevance weight is positively correlated with the importance score.

6. The method according to claim 3, characterized in that, The step of determining the target merchant name that matches the target URL address in the candidate merchant name list based on the sorting result includes: The candidate merchant with the highest matching score is determined to be the target merchant.

7. The method according to claim 1, characterized in that, Before retrieving the first candidate domain name matching the target domain name and its corresponding first candidate merchant name from the domain name database, the method further includes: The target URL address is obtained by filtering the log data reported by the client using a log filtering tool.

8. A merchant name determination device, characterized in that, The device includes: The acquisition module is used to obtain, when the target Uniform Resource Locator URL address and its corresponding target domain name are obtained, the first candidate domain name matching the target domain name and its corresponding first candidate merchant name from the domain name database. The target URL address is the URL obtained by the client scanning the QR code of the unaccepted merchant. The acquisition module is further configured to: acquire the currently running browser process based on the browser's installation path parameters; acquire the remote debugging port information of the browser process, wherein the remote debugging port information is a port number; launch the browser by executing a target command to drive chromedriver, wherein the target command includes the remote debugging port information; access the target URL address through the browser to acquire the webpage title and webpage copyright, thereby obtaining key information of the webpage; and determine the key information of the webpage as a second candidate merchant name. The retrieval module is used to access a search engine through the browser and retrieve the first keyword of the target domain name in the search engine to obtain at least one third candidate merchant name that matches the first keyword. The output module is used to sort the candidate merchant list based on relevance weight and rationality weight, and output the sorting result. The candidate merchant list includes the first candidate merchant name, the second candidate merchant name, and the at least one third candidate merchant name. The determining module is used to determine, based on the sorting results, the target merchant name in the candidate merchant name list that matches the target URL address.

9. An electronic device, characterized in that, The device includes: a processor and a memory storing computer program instructions; When the processor executes the computer program instructions, it implements the merchant name determination method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a program or instructions that, when executed by a processor, implement the merchant name determination method as described in any one of claims 1 to 7.

11. A computer program product, characterized in that, The computer program product is stored in a non-volatile storage medium, and when executed by at least one processor, the computer program product implements the merchant name determination method as described in any one of claims 1 to 7.

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