Content matching method, device, equipment, medium and program product

Abstract

The present disclosure provides a content matching method, apparatus, device, medium and program product, relating to the fields of big data and computer technology, and can be applied to the field of financial technology. The content matching method includes: in response to a query instruction for target auxiliary information, determining query content data and associated question content related to the query content data according to user operation behavior data; determining a similarity value between the auxiliary information of the associated question content and the target auxiliary information; and determining target question content that matches the target auxiliary information from the associated question content according to the similarity value.

Description

Technical Field

[0001] The present disclosure relates to the fields of big data and computer technologies, specifically to the field of information processing technologies, and more specifically to a content matching method, apparatus, device, medium, and program product. Background Art

[0002] In scenarios such as intelligent question answering, users can ask questions. For example, by extracting keywords from the question content, questions in the offline question bank can be matched, and the answer to the question with the highest keyword matching degree in the offline question bank can be pushed to the user.

[0003] In application scenarios such as banks, the accuracy and efficiency of the above technical solutions are relatively low. The reason is that, taking a bank as an example, due to its professionalism, there may be the same proper nouns and keywords such as the same or similar processing processes in multiple questions, which greatly reduces the accuracy of question matching. Summary of the Invention

[0004] In view of the above problems, the present disclosure provides a content matching method, apparatus, device, medium, and program product.

[0005] According to one aspect of the present disclosure, there is provided a content matching method, including: in response to a question instruction for target auxiliary information, determining question content data and associated question content related to the question content data according to user operation behavior data; determining a similarity value between the auxiliary information of the associated question content and the target auxiliary information; and determining target question content that matches the target auxiliary information from the associated question content according to the similarity value.

[0006] According to an embodiment of the present disclosure, the user operation behavior data includes: menu function data corresponding to the user operation behavior; determining associated question content related to the question content data according to the question content data includes: in response to a question instruction for target auxiliary information, determining question content data according to user operation behavior data; and determining the historical question content with the same menu function data as the associated question content according to the menu function data corresponding to the user operation behavior.

[0007] According to an embodiment of the present disclosure, determining a similarity value between the auxiliary information of the associated question content and the target auxiliary information includes: determining a similarity value between the auxiliary information of the associated question content and the target auxiliary information according to at least one of a string similarity parameter, an edit distance similarity parameter, and a word vector similarity parameter.

[0008] According to an embodiment of the present disclosure, at least one of the auxiliary information of the associated question content and the target auxiliary information includes specific object data; the method further includes: performing a masking process on the specific object data to obtain general object data.

[0009] According to an embodiment of the present disclosure, the specific object data includes at least one of the following: name data, identification data, and digital data; performing masking processing on the specific object data to obtain general object data includes: using a unified replacement character to replace at least one of the name data, identification data, and digital data to obtain general object data.

[0010] The content matching method according to an embodiment of the present disclosure further includes: in the case where there is no relevant associated question content in the question content data, determining question feedback data according to the question content data.

[0011] The content matching method according to an embodiment of the present disclosure further includes at least one of the following: recording each operation behavior of the user to obtain user operation behavior data; sorting the associated question content according to the similarity value and displaying the sorted associated question content.

[0012] Another aspect of the present disclosure provides a content matching device, including: a response module, a similarity value determination module, and a target question content determination module. The response module is configured to, in response to a question instruction for target auxiliary information, determine question content data and associated question content related to the question content data according to the user operation behavior data; the similarity value determination module is configured to determine a similarity value between the auxiliary information of the associated question content and the target auxiliary information; the target question content determination module is configured to determine, according to the similarity value, target question content that matches the target auxiliary information from the associated question content.

[0013] Another aspect of the present disclosure provides an electronic device, including: one or more processors; a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors are caused to execute the above content matching method.

[0014] Another aspect of the present disclosure further provides a computer-readable storage medium, on which executable instructions are stored, and when the instructions are executed by a processor, the processor is caused to execute the above content matching method.

[0015] Another aspect of the present disclosure further provides a computer program product, including a computer program, where the computer program is stored on at least one of a readable storage medium and an electronic device, and when the computer program is executed by a processor, the above content matching method is implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Through the following description of the embodiments of the present disclosure with reference to the accompanying drawings, the above content and other objects, features, and advantages of the present disclosure will become clearer. In the drawings:

[0017] Figure 1 Schematically shows an application scenario diagram of a content matching method, apparatus, device, medium, and program product according to an embodiment of the present disclosure;

[0018] Figure 2 Schematically shows a flowchart of a content matching method according to an embodiment of the present disclosure;

[0019] Figure 3 Schematically shows a flowchart of question content data of a content matching method according to another embodiment of the present disclosure and associated question content related to the question content data;

[0020] Figure 4 Schematically shows a flowchart of determining a similarity value between auxiliary information of associated question content and target auxiliary information of a content matching method according to still another embodiment of the present disclosure;

[0021] Figure 5 Schematically shows a flowchart of a content matching method according to still another embodiment of the present disclosure;

[0022] Figure 6 Schematically shows a flowchart of obtaining general object data of a content matching method according to still another embodiment of the present disclosure;

[0023] Figure 7 Schematically shows a flowchart of a content matching method according to still another embodiment of the present disclosure;

[0024] Figure 8 Schematically shows a structural block diagram of a content matching apparatus according to an embodiment of the present disclosure; and

[0025] Figure 9 Schematically shows a block diagram of an electronic device suitable for implementing a content matching method according to an embodiment of the present disclosure. Detailed implementation manners

[0026] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are merely exemplary and are not intended to limit the scope of the present disclosure. In the following detailed description, for the sake of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, obviously, one or more embodiments can also be implemented without these specific details. In addition, in the following description, descriptions of well-known structures and technologies are omitted to avoid unnecessarily confusing the concepts of the present disclosure.

[0027] The terms used herein are merely for describing specific embodiments and are not intended to limit the present disclosure. The terms "including", "comprising", etc. used herein indicate the presence of the described features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0028] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those of ordinary skill in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification, and should not be interpreted in an idealized or overly rigid manner.

[0029] In the case of using expressions such as "at least one of A, B, and C, etc.", generally, it should be interpreted according to the meaning commonly understood by those of ordinary skill in the art (for example, "a system having at least one of A, B, and C" should include, but is not limited to, a system having only A, only B, only C, having A and B, having A and C, having B and C, and / or having A, B, and C, etc.).

[0030] It should be noted that the content matching method and device determined in the embodiments of the present disclosure can be used in the financial field, and can also be used in any field other than the financial field. The embodiments of the present disclosure do not limit the application fields of the content matching method and device.

[0031] The following will be described by taking a bank application scenario as an example.

[0032] For example, the staff of a bank, as a user of a dedicated system such as a bank's credit system, can use the dedicated system to handle various credit operations for relevant individuals and enterprises, etc. When the user uses the dedicated system to perform relevant business operations, various problems may be encountered. In order to uniformly provide answers to common problems to the user, some embodiments can, for example, pre-determine a variety of common problems and corresponding answer contents, so that when the user encounters a problem, the user can adopt an online Q&A method and input a problem description. The system can extract the keywords of the problem description content, select a problem with a higher degree of matching and the corresponding answer content from the pre-determined multiple common problems, and push them to the user.

[0033] Since the credit system is a dedicated system and involves a large number of proprietary terms, when these proprietary terms are used as keywords for the user's problem description, a large number of problems may be matched. In addition, the processes of each credit operation may be very similar, and when the vocabulary related to the credit operation process is used as a keyword, a large number of problems may also be matched. Thus, for example, in the above application scenario, the user may match a large number of problems through the problem description content, but these problems may not be consistent with the problems actually expected by the user.

[0034] The credit system can also provide prompt functions for problems or operations, etc. For example, when a user browses the reply content of a certain problem, relevant prompts for the reply content of the problem can be obtained through the prompt function. For another example, when a user uses the system to perform an operation, relevant prompts for the current operation can be obtained through the prompt function.

[0035] For example, if the user has a question about the current operation, through the Q&A function of the credit system, the content of the question is uploaded to the credit system with the question description "What are the certification documents required for an enterprise to borrow M million yuan?". The credit system matches x relevant questions according to the content of the question description. When the user clicks on the i-th question, the credit system displays the reply content of this question "The certification documents required for an enterprise to borrow M million yuan are Certification Document 1, Certification Document 2, and Certification Document 3". When the credit system supports the prompt function, the prompts for this question and its reply content can be, for example, relevant definitions and explanations, such as "Certification Document 1 needs to be stamped with the enterprise seal y".

[0036] In the technical solution of the present disclosure, the processing of the collection, storage, use, processing, transmission, provision, disclosure, and application, etc. of the user's personal information involved all comply with the provisions of relevant laws and regulations, necessary confidentiality measures are taken, and public order and good customs are not violated.

[0037] In the technical solution of the present disclosure, before obtaining or collecting the user's personal information, the authorization or consent of the user is obtained.

[0038] Figure 1 An application scenario diagram of the content matching method according to an embodiment of the present disclosure is schematically shown.

[0039] As Figure 1 shown, the application scenario 100 according to this embodiment may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 is used to provide a medium for communication links between the terminal devices 101, 102, 103 and the server 105. The network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, etc.

[0040] The user can use the terminal devices 101, 102, 103 to interact with the server 105 through the network 104 to receive or send messages, etc. Various communication client applications may be installed on the terminal devices 101, 102, 103, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only for example).

[0041] The terminal devices 101, 102, 103 may be various electronic devices with a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, and desktop computers, etc.

[0042] Server 105 may be a server that provides various services. For example, it may be a background management server (merely an example) that supports websites browsed by users using terminal devices 101, 102, and 103. The background management server may analyze and process data such as user requests received, and feedback the processing results (such as web pages, information, or data obtained or generated according to user requests) to the terminal devices.

[0043] It should be noted that the content matching method provided by the embodiments of the present disclosure can generally be executed by server 105. Correspondingly, the content matching device provided by the embodiments of the present disclosure can generally be set in server 105. The content matching method provided by the embodiments of the present disclosure can also be executed by a server or a server cluster different from server 105 and capable of communicating with terminal devices 101, 102, 103 and / or server 105. Correspondingly, the content matching device provided by the embodiments of the present disclosure can also be set in a server or a server cluster different from server 105 and capable of communicating with terminal devices 101, 102, 103 and / or server 105.

[0044] It should be understood that Figure 1 the numbers of terminal devices, networks, and servers in

[0045] are merely illustrative. According to the implementation requirements, there can be any number of terminal devices, networks, and servers. Figure 1 Based on the Figures 2 to 7 scenario described below, the content matching method of the embodiments of the present disclosure will be described in detail through

[0046] Figure 2 FIG. schematically shows a flowchart of the content matching method according to an embodiment of the present disclosure.

[0047] As Figure 2 shown, the content matching method of this embodiment includes operation S210 to operation S230.

[0048] In operation S210, in response to a query instruction for target auxiliary information, according to user operation behavior data, query content data and associated question content related to the query content data are determined.

[0049] According to the content matching method of the embodiments of the present disclosure, auxiliary information can be understood as supplementary information for auxiliary understanding. For example, the auxiliary information can be directed to a certain operation, a certain question, and the corresponding answer content of the question.

[0050] Still taking the credit system in the bank application scenario as an example. For example, when a user performs a certain operation, the target auxiliary information may include prompt information for the operation, and the target auxiliary information represents how to operate currently. Or, when the user views a certain problem, the target auxiliary information may also include prompt information for the problem, and the target auxiliary information may represent the relevant explanatory content of the problem.

[0051] The question instruction for the target auxiliary information can be understood as an instruction for asking questions about the target auxiliary information. For example, the user can generate a question instruction for the target auxiliary information by clicking on the question icon for the target auxiliary information on the interface.

[0052] It can be understood that the question instruction for the target auxiliary information indicates that the user still has doubts about the target auxiliary information. The user operation behavior data is the data of the user's operation behavior, and the user operation behavior data can to a certain extent reflect the problems encountered by the user currently. Therefore, according to the content matching method of the embodiments of the present disclosure, the question content data determined according to the user operation behavior data is more accurate.

[0053] Exemplarily, for example, multiple stockpiled questions can be determined in advance, and according to the specific question content data, the associated question content related to the question content data is selected from the stockpiled questions.

[0054] In operation S220, determine the similarity value between the auxiliary information of the associated question content and the target auxiliary information.

[0055] In operation S230, according to the similarity value, determine the target question content that matches the target auxiliary information from the associated question content.

[0056] According to the content matching method of the embodiments of the present disclosure, the associated question content related to the question content data determined according to the question content data can perform a preliminary screening on, for example, the stockpiled question content, improving the accuracy of content matching. According to the similarity value between the auxiliary information of the associated question content and the target auxiliary information, a secondary screening can be performed on the associated question content. Thus, the number of determined target question content is higher and the accuracy is higher, and the probability that the target question content hits the question content expected by the user is higher, with higher content matching efficiency.

[0057] Figure 3 Schematically shows a flowchart of determining the question content data and the associated question content related to the question content data according to another embodiment of the present disclosure. The user operation behavior data includes: menu function data corresponding to the user operation behavior.

[0058] Such as Figure 3As shown, for example, the following embodiments can be used to implement the response to the question instruction for the target auxiliary information, and specific examples of determining the question content data and the associated question content related to the question content data according to the user operation behavior data.

[0059] In operation S311, in response to the question instruction for the target auxiliary information, the question content data is determined according to the user operation behavior data.

[0060] Taking the credit system in the bank application scenario as an example, it can be understood that when the user encounters a problem and asks a question during the operation of the credit system, the content of the question is most likely related to the user operation behavior. For example, when the user encounters a problem while filling in information on the interface, the question content data can correspond to the unfilled information.

[0061] Exemplarily, for example, relevant personnel can pre-determine the extraction rules for determining the question content data elements from the user operation behavior data. Thus, for example, the corresponding elements can be extracted from the user operation behavior data according to the extraction rules, and these elements can represent the question content data in a structured form.

[0062] In operation S312, according to the menu function data corresponding to the user operation behavior, the historical question content corresponding to the same menu function data is determined as the associated question content.

[0063] It can be understood that the user operation behavior can be executed through the interface. As the user's specific operation behavior changes, the interface can change accordingly, and the corresponding menu functions can be displayed on each interface.

[0064] The historical question content can be understood as the historical questions asked by the user before the current moment.

[0065] Taking the menu function data M1 corresponding to the user operation behavior as an example, the "historical question content corresponding to the same menu function data" in operation S312 can be understood as: in the historical question records (the historical question records are the historical question content data), for example, when there are R users asking questions, and the interface corresponding to the question instruction displays the menu function data M1, the corresponding historical question content of these R users' questions can be used as the associated question content.

[0066] When a user encounters a problem during the operation of the credit system and asks a question, the content of the question is most likely related to the user's operation behavior. According to the content matching method of the embodiments of the present disclosure, user operation behavior data can be utilized to accurately determine the corresponding question content data. According to the content matching method of the embodiments of the present disclosure, menu function data can be used as a screening basis. The historical questions corresponding to the same menu function data have a higher relevance. Relevant question content that is more reference-worthy for the question content data can be selected from the historical question content, with higher content matching accuracy and efficiency. In addition, the historical question content is the content of questions that have already been asked, and the relevant question content selected from the historical question content has corresponding answer content. Therefore, the content matching method of the embodiments of the present disclosure also has the ability of self-service content matching and has high availability.

[0067] Exemplarily, operation S310 is similar to the above operation S210 and will not be elaborated here. Operations S311 to S312 can be performed, for example, before the above operation S220.

[0068] Figure 4 A flowchart showing the similarity value between the auxiliary information of the relevant question content and the target auxiliary information in the content matching method according to another embodiment of the present disclosure is schematically shown.

[0069] As Figure 4 shown, for example, the following embodiments can be used to implement a specific example of determining the similarity value between the auxiliary information of the relevant question content and the target auxiliary information in S420.

[0070] In operation S421, according to at least one of the string similarity parameter, edit distance similarity parameter, and word vector similarity parameter, determine the similarity value between the auxiliary information of the relevant question content and the target auxiliary information.

[0071] It can be understood that both the auxiliary information of the relevant question content and the target auxiliary information can be stored in the form of strings.

[0072] Exemplarily, the string similarity parameter can include, for example, the Jaccard similarity parameter. For example, let A and B represent the string sets of the auxiliary information of the relevant question content and the target auxiliary information respectively. The number of intersecting characters of the two string sets is n = |A ∩ B|, and the number of characters in the union of the two sets is m = |A ∪ B|. Then the similarity value S1 measured by the Jaccard similarity between the relevant question content and the target auxiliary information is S1 = n / m.

[0073] Exemplarily, the edit distance similarity parameter may include, for example, the Levenshtein distance parameter. For example, calculate the Levenshtein distance between the string of the auxiliary information of the associated problem content and the string of the target auxiliary information as the edit distance, denoted as n; take the maximum length of the string of the auxiliary information of the associated problem content and the string of the target auxiliary information, denoted as m; then the similarity value S2 measured by the Levenshtein distance parameter between the associated problem content and the target auxiliary information is S2 = 1 - (n / m).

[0074] Exemplarily, the word vector similarity parameter may include, for example, the cosine similarity parameter.

[0075] In the case where the cosine similarity parameter is used as the word vector similarity parameter, for example, the word vector representation forms of the auxiliary information of the associated problem content and the target auxiliary information can be determined respectively through natural language processing models such as the BERT (Bidirectional Encoder Representations from Transformer) preprocessing model and the ERNIE preprocessing model, and then the cosine similarity value between the two is calculated as the word vector similarity value.

[0076] Exemplarily, in the case of including multiple of the string similarity parameter, the edit distance similarity parameter, and the word vector similarity parameter, the similarity value between the auxiliary information of the associated problem content and the target auxiliary information can be determined according to the weighted sum of the corresponding similarity parameters. For example, in the case of including the string similarity parameter, the edit distance similarity parameter, and the word vector similarity parameter, the similarity value S between the auxiliary information of the associated problem content and the target auxiliary information is S = q1*S1 + q2*S2 + q3*S3, where q1, q2, and q3 are the weight parameters of the above three similarity parameters, the weight parameters can be set, and q1, q2, and q3 are all greater than 0, and q1 + q2 + q3 = 1.

[0077] According to the content matching method of the present disclosure embodiment, through at least one similarity parameter, the similarity between the auxiliary information of the associated problem content and the target auxiliary information can be accurately measured. In the case of multiple similarity parameters, the similarity between the auxiliary information of the associated problem content and the target auxiliary information can be comprehensively and accurately determined.

[0078] Taking the credit system in the bank application scenario as an example, the string similarity parameter can measure the similarity between the auxiliary information of the associated problem content and the target auxiliary information in terms of the string coincidence ratio. The edit distance similarity parameter can characterize the difference degree between the string of the auxiliary information of the associated problem content and the string of the target auxiliary information. The word vector similarity parameter can reflect the difference degree between the auxiliary information of the associated problem content and the target auxiliary information from the perspective of more representative features.

[0079] Exemplarily, operation S420 is similar to the above operation S220 and will not be elaborated here. Operation S421 can be performed, for example, between the above operation S210 and operation S230.

[0080] Figure 5 The flowchart of the content matching method according to another embodiment of the present disclosure is schematically shown. At least one of the auxiliary information of the associated problem content and the target auxiliary information includes specific object data.

[0081] Such as Figure 5 shown, the content matching method 500 according to another embodiment of the present disclosure may include, for example, operation S540.

[0082] In operation S540, the specific object data is masked to obtain general object data.

[0083] The specific object data can be understood as data with specific meanings or representing specific objects. The general object data has wide adaptability.

[0084] It can be understood that the content matching method of the embodiments of the present disclosure determines the target problem content matching the target auxiliary information from the associated problem content based on the similarity value between the auxiliary information of the associated problem content and the target auxiliary information. When at least one of the auxiliary information of the associated problem content and the target auxiliary information includes specific object data, the similarity regarding the specific object data between the two will also affect the similarity value between the target auxiliary information and the auxiliary information of the associated problem content. In fact, the similarity regarding the specific object data can be ignored.

[0085] For example, still taking the credit system in the bank application scenario as an example, at least one of the auxiliary information associated with the problem content and the target auxiliary information may include specific object data such as a specific customer name, customer code, etc. In fact, even if the specific object data such as the customer name and customer code changes, it will not affect the determination of the target problem content expected by the user. Therefore, according to the content matching method of the embodiments of the present disclosure, by masking the specific object data, the similarity regarding the specific object data between the auxiliary information of the associated problem content and the target auxiliary information can be stripped. The obtained general object data has wide adaptability and will not affect the accuracy of determining the target problem content, and has a higher content matching efficiency.

[0086] Exemplarily, the content matching method 500 according to the embodiments of the present disclosure may include the above operations S210 to S230. The operation S540 may be executed, for example, after the above operation S210 or before the operation S220.

[0087] Figure 6 Schematically shows a flowchart of obtaining general object data of the content matching method according to another embodiment of the present disclosure. The specific object data includes at least one of the following: name data, identification data, and digital data.

[0088] As Figure 6 shown, the masking process of the specific object data in operation S640 to obtain general object data includes operation S641.

[0089] In operation S641, at least one of the name data, identification data, and digital data is replaced with a unified replacement character to obtain general object data.

[0090] Exemplarily, the unified replacement character may include a space character, for example.

[0091] Exemplarily, when the digital data is a decimal or a negative number, for example, the decimal point of the decimal or the negative sign of the negative number may also be replaced with the unified replacement character.

[0092] Exemplarily, when at least one of the name data, identification data, and digital data is replaced to obtain general object data with a continuous plurality of unified replacement characters, the continuous plurality of unified replacement characters may be merged into one unified replacement character until the general object data does not include a continuous plurality of unified replacement characters.

[0093] Specific object data mostly exists in the form of names, identifiers, and numbers. According to the content matching method of the embodiments of the present disclosure, by using a unified replacement character to replace at least one of the name data, identifier data, and number data, it is possible to adapt to various conventional specific object data, and the obtained general object data has wide adaptability.

[0094] Exemplarily, operation S640 is similar to the above-mentioned operation S540 and will not be elaborated here. Operation S641 can be executed, for example, after the above-mentioned operation S220 and before operation S230.

[0095] Figure 7 A flowchart of a content matching method according to another embodiment of the present disclosure is schematically shown.

[0096] Such as Figure 7 As shown, the content matching method 700 according to another embodiment of the present disclosure may include operation S750.

[0097] In operation S750, in the case where there is no relevant associated question content in the question content data, question feedback data is determined according to the question content data. The question feedback data can be understood as data fed back to relevant personnel such as question answers.

[0098] For example, when the historical question content corresponding to the same menu function data is determined as the associated question content according to the menu function data corresponding to the user operation behavior, if there is no relevant associated question content in the question content data, it indicates that there is no historical question content related to the question content data. The question feedback data determined according to the content matching method of the embodiments of the present disclosure can be used to feed back to relevant personnel, for example. Subsequently, relevant personnel can answer the question content data, for example, to form a closed loop of the processing flow for the question content data. The answered content can be used as the answer content for new historical questions, with higher content matching efficiency.

[0099] Exemplarily, the question content data may include, for example, screenshot data of the menu function page corresponding to the user operation behavior. Thus, the question content data can intuitively represent the user's current question, facilitating relevant personnel to accurately answer according to the prompt content data. Exemplarily, operation S750 can be executed, for example, after the above-mentioned operation S210.

[0100] Figure 7 A schematic diagram of a content matching method according to another embodiment of the present disclosure is also schematically shown.

[0101] Such as Figure 7 As shown, the content matching method according to another embodiment of the present disclosure may further include at least one of operations S760 to S770.

[0102] In operation S760, each operation behavior of the user is recorded to obtain user operation behavior data.

[0103] Still taking the credit system in the bank application scenario as an example, exemplarily, for example, after the user logs in to the credit system, the user's operations can be tracked and specific object data such as the menu function currently used by the user, the affiliated institution, the customer code, and the customer name can be marked and recorded in the session.

[0104] In operation S770, according to the similarity value, the associated problem content is sorted and the sorted associated problem content is displayed.

[0105] Exemplarily, for example, the associated problem content can be sorted and displayed in descending order of the similarity value.

[0106] According to the content matching method of the embodiments of the present disclosure, by recording each operation behavior of the user, accurate user operation behavior data can be obtained in real time, which is convenient for subsequent determination of, for example, the question content data and the associated problem content related to the question content data.

[0107] According to the content matching method of the embodiments of the present disclosure, by sorting the associated problem content according to the similarity value and displaying the sorted associated problem content, it is more in line with the viewing habits of users and is convenient for users to quickly and efficiently view the desired problem content.

[0108] Exemplarily, operation S760 can be executed, for example, before the above operation S210. Operation S770 can be executed, for example, after the above operation S220.

[0109] Based on the above content matching method, the present disclosure also provides a content matching device. The following will be combined with Figure 8 Describe this device in detail.

[0110] Figure 8 Schematically shows a structural block diagram of a content matching device according to an embodiment of the present disclosure.

[0111] As Figure 8 shown, the content matching device 800 of this embodiment includes a response module 810, a similarity value determination module 820, and a target problem content determination module 830.

[0112] The response module 810 is configured to respond to a question instruction for target auxiliary information, and determine question content data and associated problem content related to the question content data according to user operation behavior data.

[0113] The similarity value determination module 820 is configured to determine a similarity value between the auxiliary information of the associated problem content and the target auxiliary information.

[0114] A target question content determination module 830, configured to determine, according to the similarity value, target question content that matches the target auxiliary information from the associated question content.

[0115] According to an embodiment of the present disclosure, the user operation behavior data includes: menu function data corresponding to the user operation behavior. The response module may include: a question content data determination sub-module and an associated question content determination sub-module.

[0116] The question content data determination sub-module is configured to determine question content data according to the user operation behavior data in response to a question instruction for the target auxiliary information.

[0117] The associated question content determination sub-module is configured to determine, according to the menu function data corresponding to the user operation behavior, historical question content with the same menu function data as the associated question content.

[0118] According to an embodiment of the present disclosure, the similarity value determination module may include: a similarity value determination sub-module.

[0119] The similarity value determination sub-module is configured to determine a similarity value between the auxiliary information of the associated question content and the target auxiliary information according to at least one of a string similarity parameter, an edit distance similarity parameter, and a word vector similarity parameter.

[0120] According to an embodiment of the present disclosure, at least one of the auxiliary information of the associated question content and the target auxiliary information includes specific object data. The content matching device may further include: a general object data determination module.

[0121] The general object data determination module is configured to perform a masking process on the specific object data to obtain general object data.

[0122] According to an embodiment of the present disclosure, the specific object data includes at least one of the following: name data, identification data, and digital data. The general object data determination module may include: a general object data determination sub-module.

[0123] The general object data determination sub-module is configured to use a unified replacement character to replace at least one of the name data, the identification data, and the digital data to obtain general object data.

[0124] According to an embodiment of the present disclosure, the content matching device may further include: a feedback module.

[0125] The feedback module is configured to determine question feedback data according to the question content data when there is no associated question content related to the question content data.

[0126] The content matching device according to an embodiment of the present disclosure may further include at least one of the following: a recording module and a sorting module.

[0127] The recording module is configured to record each operation behavior of the user to obtain user operation behavior data.

[0128] The sorting module is configured to sort the associated problem content according to the similarity value and display the sorted associated problem content.

[0129] According to an embodiment of the present disclosure, any multiple modules among the response module 810, the similarity value determination module 820, and the target problem content determination module 830 may be combined and implemented in one module, or any one of them may be split into multiple modules. Alternatively, at least part of the functions of one or more of these modules may be combined with at least part of the functions of other modules and implemented in one module. According to an embodiment of the present disclosure, at least one of the response module 810, the similarity value determination module 820, and the target problem content determination module 830 may be at least partially implemented as a hardware circuit, such as a field programmable gate array (FPGA), a programmable logic array (PLA), a system on chip, a system on a substrate, a system in a package, an application specific integrated circuit (ASIC), or any other reasonable manner of integrating or packaging circuits, etc., implemented by hardware or firmware, or implemented in any one of the three implementation manners of software, hardware, and firmware, or in an appropriate combination of any several of them. Alternatively, at least one of the response module 810, the similarity value determination module 820, and the target problem content determination module 830 may be at least partially implemented as a computer program module, and when the computer program module is run, it can execute the corresponding functions.

[0130] It should be understood that the embodiments of the device part of the present disclosure correspond to the same or similar embodiments of the method part of the present disclosure, and the technical problems solved and the technical effects achieved are also the same or similar. The present disclosure will not be elaborated herein.

[0131] Figure 9 A block diagram of an electronic device suitable for implementing the content matching method according to an embodiment of the present disclosure is schematically shown.

[0132] As Figure 9As shown, the electronic device 900 according to an embodiment of the present disclosure includes a processor 901, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 902 or a program loaded from a storage section 908 into a random access memory (RAM) 903. The processor 901 can include, for example, a general microprocessor (such as a CPU), an instruction set processor, and / or a related chipset, and / or a dedicated microprocessor (such as an application specific integrated circuit (ASIC)), etc. The processor 901 can also include on-board memory for caching purposes. The processor 901 can include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0133] In the RAM 903, various programs and data required for the operation of the electronic device 900 are stored. The processor 901, the ROM 902, and the RAM 903 are connected to each other via a bus 904. The processor 901 performs various operations of the method flow according to an embodiment of the present disclosure by executing the program in the ROM 902 and / or the RAM 903. It should be noted that the program can also be stored in one or more memories other than the ROM 902 and the RAM 903. The processor 901 can also perform various operations of the method flow according to an embodiment of the present disclosure by executing the program stored in the one or more memories.

[0134] According to an embodiment of the present disclosure, the electronic device 900 can further include an input / output (I / O) interface 905, and the input / output (I / O) interface 905 is also connected to the bus 904. The electronic device 900 can further include one or more of the following components connected to the I / O interface 905: an input section 906 including a keyboard, a mouse, etc.; an output section 907 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc. and a speaker, etc.; a storage section 908 including a hard disk, etc.; and a communication section 909 including a network interface card such as a LAN card, a modem, etc. The communication section 909 performs communication processing via a network such as the Internet. A drive 910 is also connected to the I / O interface 905 as needed. A removable medium 911, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 910 as needed so that a computer program read from it can be installed into the storage section 908 as needed.

[0135] The present disclosure also provides a computer-readable storage medium, which can be included in the device / device / system described in the above embodiment; or can exist separately without being assembled into the device / device / system. The above computer-readable storage medium carries one or more programs, and when the one or more programs are executed, the method according to an embodiment of the present disclosure is implemented.

[0136] According to an embodiment of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, which may include, for example, but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In the present disclosure, the computer-readable storage medium may be any tangible medium that contains or stores a program, and this program may be used by or in conjunction with an instruction execution system, apparatus, or device. For example, according to an embodiment of the present disclosure, the computer-readable storage medium may include one or more memories other than the above-described ROM 902 and / or RAM 903 and / or ROM 902 and RAM 903.

[0137] An embodiment of the present disclosure further includes a computer program product, which includes a computer program that contains program code for executing the method shown in the flowchart. When the computer program product runs in a computer system, the program code is used to cause the computer system to implement the method provided by the embodiment of the present disclosure.

[0138] When the computer program is executed by the processor 901, it executes the above functions defined in the system / apparatus of the embodiment of the present disclosure. According to an embodiment of the present disclosure, the above-described systems, apparatuses, modules, units, etc. may be implemented by computer program modules.

[0139] In one embodiment, the computer program may rely on tangible storage media such as optical storage devices and magnetic storage devices. In another embodiment, the computer program may also be transmitted and distributed in the form of a signal on a network medium, and be downloaded and installed through the communication part 909, and / or be installed from the removable medium 911. The program code included in the computer program may be transmitted by any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0140] In such an embodiment, the computer program may be downloaded and installed from the network through the communication part 909, and / or be installed from the removable medium 911. When the computer program is executed by the processor 901, it executes the above functions defined in the system of the embodiment of the present disclosure. According to an embodiment of the present disclosure, the above-described systems, devices, apparatuses, modules, units, etc. may be implemented by computer program modules.

[0141] According to embodiments of the present disclosure, program code for executing the computer programs provided by the embodiments of the present disclosure may be written in any combination of one or more programming languages. Specifically, these computing programs may be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. Programming languages include, but are not limited to, such as Java, C++, Python, the "C" language, or similar programming languages. The program code may be executed entirely on the user's computing device, partially on the user's device, partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user's computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., by connecting through the Internet using an Internet service provider).

[0142] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code that contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram or flowchart, and combinations of blocks in the block diagram or flowchart, may be implemented by a dedicated hardware-based system for performing the specified functions or operations, or may be implemented by a combination of dedicated hardware and computer instructions.

[0143] Those skilled in the art can understand that the features recited in the various embodiments and / or claims of the present disclosure can be combined or combined in various ways, even if such combinations or combinations are not explicitly recited in the present disclosure. In particular, without departing from the spirit and teachings of the present disclosure, the features recited in the various embodiments and / or claims of the present disclosure can be combined and combined in various ways. All such combinations and / or combinations fall within the scope of the present disclosure.

[0144] The embodiments of the present disclosure have been described above. However, these embodiments are merely for illustrative purposes and not for limiting the scope of the present disclosure. Although the embodiments have been described separately above, this does not mean that the measures in each embodiment cannot be used advantageously in combination. The scope of the present disclosure is defined by the appended claims and their equivalents. Without departing from the scope of the present disclosure, those skilled in the art can make various substitutions and modifications, and these substitutions and modifications should all fall within the scope of the present disclosure.

Claims

1. A content matching method, comprising: Responding to a query instruction for target auxiliary information, determining query content data and associated question content related to the query content data according to user operation behavior data; Determining a similarity value between the auxiliary information of the associated question content and the target auxiliary information; And Determining target question content that matches the target auxiliary information from the associated question content according to the similarity value; Wherein, the user operation behavior data includes: menu function data corresponding to user operation behaviors; the responding to a query instruction for target auxiliary information and determining query content data and associated question content related to the query content data according to user operation behavior data includes: Responding to a query instruction for the target auxiliary information, determining the query content data according to the user operation behavior data; and Determining historical question content with the same menu function data as the associated question content according to the menu function data corresponding to the user operation behavior.

2. The method according to claim 1, wherein The determining a similarity value between the auxiliary information of the associated question content and the target auxiliary information includes: Determining a similarity value between the auxiliary information of the associated question content and the target auxiliary information according to at least one of a string similarity parameter, an edit distance similarity parameter, and a word vector similarity parameter.

3. The method according to claim 1, wherein, At least one of the auxiliary information of the associated question content and the target auxiliary information includes specific object data; the method further includes: Performing a masking process on the specific object data to obtain general object data.

4. The method according to claim 3, wherein, The specific object data includes at least one of the following: name data, identification data, and digital data; the performing a masking process on the specific object data to obtain general object data includes: Using a unified replacement character to replace at least one of the name data, the identification data, and the digital data to obtain the general object data.

5. The method according to any one of claims 1-4, further comprising: In the case where there is no associated question content related to the query content data, determining question feedback data according to the query content data.

6. The method according to any one of claims 1-4, further comprising at least one of the following: Recording each operation behavior of the user to obtain the user operation behavior data; Sorting the associated question content according to the similarity value and displaying the sorted associated question content.

7. A content matching device, comprising: A response module, configured to respond to a query instruction for target auxiliary information, and determine query content data and associated question content related to the query content data according to user operation behavior data; A similarity value determination module, configured to determine a similarity value between the auxiliary information of the associated question content and the target auxiliary information; And A target question content determination module, configured to determine target question content that matches the target auxiliary information from the associated question content according to the similarity value; Among them, the user operation behavior data includes: menu function data corresponding to the user operation behavior; the determining of the question content data and the associated question content related to the question content data in response to a question instruction for the target auxiliary information includes: Determining the question content data according to the user operation behavior data in response to a question instruction for the target auxiliary information; and Determining the historical question content corresponding to the same menu function data as the associated question content according to the menu function data corresponding to the user operation behavior.

8. An electronic device, comprising: One or more processors; A storage device for storing one or more programs, wherein, when the one or more programs are executed by the one or more processors, the one or more processors are caused to execute the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, having stored thereon executable instructions that, when executed by a processor, cause the processor to execute the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, the computer program being stored on at least one of a readable storage medium and an electronic device, and when the computer program is executed by a processor, implementing the method according to any one of claims 1 to 6.

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