Data query method and device

Abstract

The invention discloses a data query method and device, and relates to the technical field of big data. A specific embodiment of the method comprises the following steps: in response to a received data query request, obtaining user consultation information corresponding to the data query request; carrying out keyword extraction on the user consultation information, and based on an extraction result, finding out a target plug-in corresponding to the extraction result from a pre-configured plug-in list; performing data query according to the extraction result by utilizing the target plug-in to obtain a data query result; according to the specific implementation mode, the related data of the user consultation information can be automatically queried, the query speed is high, and the efficiency is high.

Description

Technical Field

[0001] The present invention relates to the field of big data technology, and in particular to a method and device for data query. Background Art

[0002] At present, relevant data of user consultation information needs to be manually located in the corresponding business system for query. When the data is large or complex, it is necessary to switch to different business systems. The data query process depends on the manual proficiency of the business system and takes a lot of time and effort.

[0003] In the process of implementing the present invention, the inventors found that there are at least the following problems in the related art:

[0004] It is impossible to automatically query the relevant data of the user's consultation information, and the query takes a long time and has low query efficiency. Summary of the invention

[0005] In view of this, an embodiment of the present invention provides a data query method, which can automatically query relevant data of user consultation information with fast query speed and high efficiency.

[0006] To achieve the above object, according to one aspect of an embodiment of the present invention, a method for data query is provided, comprising:

[0007] In response to the received data query request, obtaining user consultation information corresponding to the data query request;

[0008] Perform keyword extraction on the user inquiry information, and based on the extraction result, find a target plug-in corresponding to the extraction result from a pre-configured plug-in list;

[0009] The target plug-in is used to perform data query according to the extraction result to obtain a data query result.

[0010] Furthermore, keyword extraction is performed on the user consultation information, including:

[0011] The user consultation information is preprocessed; the preprocessing includes at least one of the following: text cleaning, missing value completion, and word form normalization.

[0012] Extract keywords from the preprocessed user consultation information based on the keyword extraction algorithm;

[0013] The keywords are screened to obtain the extraction results.

[0014] Furthermore, the pre-configured plug-in list is obtained by the following steps:

[0015] Performing function switch configuration on at least one predetermined plug-in to obtain a configuration result; wherein the function switch includes enabling and / or disabling the plug-in;

[0016] A plug-in list is generated based on the configuration result.

[0017] Furthermore, after generating the plug-in list based on the configuration result, the method further includes:

[0018] The plug-in list is integrated into the front-end page. After the front-end page is loaded, the plug-ins in the plug-in list can automatically register plug-ins through a registration mechanism and monitor data query operations.

[0019] Furthermore, the method further comprises:

[0020] Setting a static component at a specified position on the front-end page, wherein the specified position is determined by setting a top offset attribute, a left offset attribute, a right offset attribute, or a bottom offset attribute in a cascading style sheet;

[0021] The plug-in with the function switch enabled is embedded into the static component.

[0022] Furthermore, after obtaining the data query result, it also includes:

[0023] A data query result display area is created, and a function button is set on the display area, wherein the function button is used to send the data query result to the user.

[0024] Further, obtaining user consultation information corresponding to the data query request includes:

[0025] Parameter information of the user consultation information is parsed from the data query request, and the user consultation information is acquired according to the parameter information.

[0026] According to a second aspect of an embodiment of the present invention, a data query device is provided, including:

[0027] An acquisition module, configured to, in response to a received data query request, acquire user consultation information corresponding to the data query request;

[0028] A search module, used to extract keywords from the user consultation information, and based on the extraction results, search for a target plug-in corresponding to the extraction results from a pre-configured plug-in list;

[0029] The query module is used to use the target plug-in to perform data query according to the extraction result to obtain a data query result.

[0030] According to a third aspect of an embodiment of the present invention, there is provided an electronic device, including:

[0031] one or more processors;

[0032] a memory for storing one or more programs,

[0033] When the one or more programs are executed by the one or more processors, the one or more processors are enabled to implement the method described in any one of the above embodiments.

[0034] According to a fourth aspect of an embodiment of the present invention, a computer-readable medium is provided, on which a computer program is stored, and when the program is executed by a processor, the method described in any one of the above embodiments is implemented.

[0035] An embodiment of the above invention has the following advantages or beneficial effects: by responding to a received data query request, user consultation information corresponding to the data query request is obtained; keywords are extracted from the user consultation information, and based on the extraction result, a target plug-in corresponding to the extraction result is found from a pre-configured plug-in list; data query is performed according to the extraction result using the target plug-in to obtain a data query result; relevant data of the user consultation information can be automatically queried, with fast query speed and high efficiency.

[0036] The further effects of the above-mentioned non-conventional optional manner will be described below in conjunction with the specific implementation manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The accompanying drawings are used to better understand the present invention and do not constitute an improper limitation of the present invention.

[0038] Figure 1 is a schematic diagram of the main process of the data query method according to an embodiment of the present invention;

[0039] Figure 2 It is a schematic diagram of the main process of a data query method according to a reference embodiment of the present invention;

[0040] Figure 3 is a schematic diagram of the main process of a data query method according to another reference embodiment of the present invention;

[0041] Figure 4 is a schematic diagram of the main process of a data query method according to another reference embodiment of the present invention;

[0042] Figure 5 is a schematic diagram of main modules of a data query device according to an embodiment of the present invention;

[0043] Figure 6 is an exemplary system architecture diagram to which embodiments of the present invention may be applied;

[0044] Figure 7 It is a schematic diagram of the structure of a computer system of a terminal device or a server suitable for implementing an embodiment of the present invention. DETAILED DESCRIPTION

[0045] The following is a description of exemplary embodiments of the present invention in conjunction with the accompanying drawings, including various details of the embodiments of the present invention to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the present invention. Similarly, for clarity and conciseness, the description of well-known functions and structures is omitted in the following description.

[0046] It should be noted that the acquisition, storage and application of personal information etc. involved in the embodiments of the present invention are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0047] Currently, relevant data of user consultation information needs to be manually located to the corresponding business system for query. For example, for the received user consultation information, online customer service needs to open multiple external business systems to query data in order to answer the questions raised by the user. The online customer service needs to be familiar with all business systems, otherwise it is impossible to accurately locate which business system the data to be queried in the user consultation information comes from. The data query process depends on the manual proficiency in the business system. When the data is large or complex, it is necessary to switch to different business systems, which takes a lot of time and effort.

[0048] In view of this, according to one aspect of an embodiment of the present invention, a method for data query is provided. Figure 1 FIG. 1 is a schematic diagram of the main process of the data query method according to an embodiment of the present invention. Figure 1 As shown, the data query method according to an embodiment of the present invention includes:

[0049] Step S101, in response to a received data query request, obtaining user consultation information corresponding to the data query request.

[0050] Among them, the data query request is a request sent by a human (such as customer service) or system to obtain specific data or information, which can be issued through a network protocol, database query language, API (Application Programming Interface) call or other communication methods; the data query request includes: a request method, which is used to instruct the server to perform different operations, such as the HTTP protocol (Hypertext Transfer Protocol); a request address, which is a path or interface address pointing to a server-side resource, such as a URL (Uniform Resource Locator); a request parameter, which is used to specify additional information of the request details, and the request parameter can be a query string parameter, a request body parameter, a request header information, etc.; a request header information, which is some additional information of the request, such as user agent information, accepted data types, authorization information, etc.; identity authentication information, which is used to verify the legitimacy of the request and return the corresponding data, etc.

[0051] The user consultation information corresponding to the above data query request refers to the consultation or question information raised by the user associated with the data query request. User consultation information is the text or voice information left by the user in the system, which is used to request specific data, services or solve specific problems from the system. It can specifically include the following: the specific questions or request content raised by the user during the consultation, such as a text description, keywords, problem description, demand description and other forms of information; the user's identity information, used to identify which user the request comes from, such as the user ID (Identifier) ​​or user name; the user's request purpose or behavioral intention, such as the user wants to view the information of a certain product, check the order status, seek help or advice, etc.; other additional information, such as the user's context, device information, geographic location information, etc.

[0052] Step S102: extract keywords from the user inquiry information, and based on the extraction result, find out the target plug-in corresponding to the extraction result from a pre-configured plug-in list.

[0053] When processing user consultation information, keyword extraction is to identify words or phrases with specific meanings or important for answering questions from the text or voice information input by the user. The keywords can help the system better understand the user's needs, so as to conduct targeted data query, business processing or service response. For example, a user asks a question about a product in the customer service system: "What promotions are there recently?" Then the keywords that can be extracted include "promotions", "recently", "products" and other words. The above keywords can help the system locate plug-ins or business logic related to promotions, so as to provide users with relevant information or help.

[0054] The plug-in list is a list or collection of plug-ins (also called modules, components or functional blocks) pre-configured in the system. The plug-in list contains all available plug-ins in the system. Each plug-in corresponds to a function or service in the system and can be called and used by the system. In customer service systems or other software systems, the plug-in list is used to manage and organize various functional modules or services in the system. The pre-configured plug-in list may include but is not limited to the following: functional plug-ins, plug-ins used to process specific functions or business logic, such as order management plug-ins, promotion plug-ins, customer information plug-ins, etc.; service plug-ins, plug-ins used to provide specific services, such as payment service plug-ins, geo-location service plug-ins, SMS notification service plug-ins, etc.; tool plug-ins, plug-ins used to provide tool functions or auxiliary functions, such as data analysis plug-ins, report generation plug-ins, logging plug-ins, etc.; third-party plug-ins, plug-ins developed by third parties, can expand the functions and services of the system, such as social media integration plug-ins, payment gateway plug-ins, map navigation plug-ins, etc.; custom plug-ins, plug-ins customized according to system requirements or users to meet specific business needs or functional requirements.

[0055] When the system receives user inquiry information, it can use natural language processing technology to extract keywords from the user inquiry information, such as part-of-speech tagging, stem extraction, stop word filtering and other operations; analyze and process the extracted keywords or phrases, such as using algorithms or rule matching to filter and sort keywords to improve the quality of the extraction results; match the corresponding target plug-in in the pre-configured list of the above plug-ins according to the extraction results, such as by establishing a mapping relationship between keywords and plug-ins or configuring rules to implement matching logic; before determining the target plug-in to be called, the status of the target plug-in (such as enabled or disabled), permissions and other information can also be further checked to ensure that the plug-in can be called normally.

[0056] Step S103: Utilize the target plug-in to perform data query according to the extraction result to obtain a data query result.

[0057] After determining the target plug-in, call the interface or function of the target plug-in to perform data query or business processing corresponding to the extraction result. The target plug-in can access external systems, databases, or call API interfaces to obtain data related to user consultation; the target plug-in processes the obtained data query results, such as data format conversion, information filtering, content integration, etc.; the processed data query results are returned to the system. The data query results can be in the form of text information, chart data, multimedia content, etc., and are displayed to users according to needs or processed for the next step. For example, the data query results can be returned to the front-end for display, or returned to other systems or services through the back-end interface.

[0058] For example, a user asks: "What is the inventory status of product XYZ?" The customer service right-clicks the query text, and the system extracts the keywords "inventory" and "XYZ" based on the query; the system calls the "inventory query plug-in" and passes the keyword "XYZ" as a parameter to the plug-in. The "inventory query plug-in" sends a request to the ERP system (Enterprise Resource Planning System) to obtain the inventory data of product "XYZ". The ERP system processes the request and returns the inventory data to the plug-in; the plug-in obtains the inventory data returned by the ERP system, for example: "The current inventory of product XYZ is 100 units."

[0059] The embodiment of the present invention obtains user consultation information corresponding to the data query request by responding to the received data query request; performs keyword extraction on the user consultation information, and based on the extraction result, searches for the target plug-in corresponding to the extraction result from a pre-configured plug-in list; uses the target plug-in to perform data query according to the extraction result to obtain a data query result; and can automatically query the relevant data of the user consultation information with fast query speed and high efficiency.

[0060] Optionally, Figure 2 FIG. 1 is a schematic diagram of the main process of a method for data query according to a reference embodiment of the present invention. Figure 2 As shown, extracting keywords from the user consultation information includes:

[0061] Step S201, preprocessing the user consultation information; the preprocessing includes at least one of the following: text cleaning, missing value completion, and word form normalization.

[0062] Step S202, extracting keywords from the pre-processed user consultation information based on a keyword extraction algorithm;

[0063] Step S203, screening the keywords to obtain the extraction results.

[0064] Among them, step S201 can pre-process the above-mentioned user consultation information through the following operations: text cleaning, missing value completion, word form normalization, stem extraction, word form restoration, spelling check and correction, word segmentation, case processing, specific word replacement, text merging, etc. Among them, text cleaning is to remove noise data such as special characters, punctuation marks, HTML tags, etc. in the text to ensure the accuracy and stability of subsequent keyword extraction. Missing value completion is to use default values, related information or other text completion methods to fill in the missing part of the text content to ensure that the complete text data is used for keyword extraction. Word form normalization is to perform stem extraction or word form restoration on the words in the text, unifying different forms of the same word into a basic form.

[0065] After the preprocessing is completed, in step S202, keywords are extracted from the preprocessed user consultation information by a keyword extraction algorithm. Different algorithms and models based on rules, statistics, machine learning, etc. can be used to identify and extract words or phrases that are important or represent themes in the text as keywords. Specifically, the keyword extraction algorithm includes but is not limited to: TF-IDF algorithm (Term Frequency-Inverse Document Frequency), which measures the importance of words by the frequency of words in the document and the inverse document frequency in the entire corpus; LDA (Latent Dirichlet Allocation) topic model algorithm, which determines keywords by discovering themes in the document; machine learning-based methods, such as naive Bayes, support vector machines, etc., identify keywords by training models; deep learning-based methods, such as recurrent neural networks, long short-term memory networks, etc., use deep learning models to extract keywords.

[0066] In step S203, the keywords extracted in step S202 are screened to obtain the extraction result. The screening process can be carried out according to methods such as business requirements, algorithm settings, or semantic analysis. Keywords that are relevant to the user's consultation information and have a relatively high amount of information are retained, while meaningless or redundant words are discarded, so as to obtain an accurate and effective keyword extraction result. By way of example, stop words are removed. Stop words refer to words that frequently appear in the text but usually do not contain useful information, such as "de", "shi", "zai", etc.; also, for example, filtering is performed according to the frequency of words appearing in the text, and words with a relatively high or low frequency are retained as keywords; filtering is performed according to the length of the words, and words with a moderate length are retained as keywords, such as retaining words with 2 to 5 characters; filtering is performed according to the part of speech of the words, and words with a specific part of speech are retained as keywords, such as nouns, verbs, etc.; filtering is performed according to the semantic information of the words, and words with a clear semantics are retained as keywords to avoid ambiguous or inaccurate words being selected as keywords; for texts in a specific field, filtering is performed to retain words related to that field as keywords to improve the accuracy and pertinence of the keywords. The specific filtering form is not specifically limited in the embodiments of the present invention.

[0067] In the embodiments of the present invention, first, the user's consultation information is preprocessed. Based on the preprocessed data, a keyword extraction algorithm is used to extract keywords, and then irrelevant words are removed through screening to obtain the extraction result, which can improve the accuracy and comprehensiveness of the keywords and also improve the accuracy of subsequent analysis and query.

[0068] Optionally, Figure 3 is a schematic diagram of the main process of the data query method according to another referenceable embodiment of the present invention. As Figure 3 shown, the preconfigured plug-in list is obtained through the following steps:

[0069] Step S301, perform function switch configuration on at least one pre-determined plug-in to obtain a configuration result; wherein, the function switch includes enabling and / or disabling of the plug-in;

[0070] Step S302, generate a plug-in list based on the configuration result.

[0071] Among them, before step S301, the functional requirements of the business department or system users for the system can also be collected to determine the plug-ins for implementing the functions. Step S301 can develop a plug-in configuration interface for managing and configuring the enabling status of each plug-in. The configuration interface displays the name, description, and current enabling status of each plug-in, and provides corresponding operation options, such as providing enabling and disabling function switch options for each plug-in. Users can select to enable or disable a certain plug-in according to their needs and save the configuration result.

[0072] Step S302 reads the enabled status information of each plug-in from the configuration result; generates a plug-in list based on the read configuration information, wherein the plug-in list includes enabled plug-ins and related information such as name, version, description, etc. The plug-in list can be saved in a configuration file or database of the system, and when the system is running, the enabled plug-ins are dynamically loaded according to the generated plug-in list.

[0073] The embodiment of the present invention performs flexible function switch configuration for predetermined plug-ins, can enable or disable plug-ins according to actual needs, generate a plug-in list based on the configuration results, improve the flexibility and performance of the system, enable the system to dynamically load and manage plug-ins according to the configured plug-in list, and effectively improve the scalability and maintainability of the system.

[0074] Optionally, after step S302 generates a plug-in list based on the configuration result, the method further includes:

[0075] The plug-in list is integrated into the front-end page. After the front-end page is loaded, the plug-ins in the plug-in list can automatically register plug-ins through a registration mechanism and monitor data query operations.

[0076] Specifically, according to the generated plug-in list, the plug-in list is integrated into the corresponding position of the front-end page by introducing the configuration file of the plug-in list in the page or dynamically obtaining the plug-in list through the back-end interface; the registration and monitoring logic is executed through the front-end framework or life cycle function, and after the front-end page is fully loaded, the plug-in registration and monitoring operations are triggered, and the plug-in components or related plug-in information are registered to the front-end application according to the configuration information in the plug-in list; after registration is completed, data query operations are monitored, that is, when the customer service performs data query or other related operations, the plug-in can communicate with the back-end interface and perform data processing and other operations according to the registered logic.

[0077] For example, in an online customer service system, you can introduce plug-in components and SDK (Software Development Kit) in the page header of the main project. The main project creates a new route and uses the customer service plug-in component. After the page is loaded, it will automatically register and listen for the customer service plug-in that the user wants to use. You only need to call the business data in the customer service plug-in SOA (Service-Oriented Architecture) inside the plug-in to realize the call of the plug-in and the acquisition and processing of business data.

[0078] The embodiment of the present invention integrates the generated plug-in list into the front-end page and implements automatic registration and monitoring functions, thereby enhancing the flexibility and interactivity of the system and improving user experience and system performance.

[0079] Optionally, Figure 4 FIG. 1 is a schematic diagram of the main process of a method for data query according to another reference embodiment of the present invention. Figure 4 As shown, the method also includes:

[0080] Step S401, setting a static component at a designated position of the front-end page, wherein the designated position is determined by setting a top offset attribute, a left offset attribute, a right offset attribute, or a bottom offset attribute in a cascading style sheet;

[0081] Step S402: embed the plug-in with the function switch enabled into the static component.

[0082] Among them, you can use the offset properties in the Cascading Style Sheets (CSS) to control the position and layout of static components on the front-end page. For example, use the top offset property (top) to place the component at the top of the page, the left offset property (left) to place it on the left side of the page, the right offset property (right) to place it on the right side of the page, or the bottom offset property (bottom) to place the component at the bottom of the page. That is, by adjusting the value of the offset property, you can place the component anywhere on the page and ensure that the static component can be displayed and laid out correctly when the page is loaded.

[0083] Step S402 can introduce the plug-in component into the front-end code and nest the plug-in component inside the static component, so that the plug-in can be correctly rendered and displayed after the page is loaded, and can interact with other page elements. Embedding the plug-in into the static component can also improve the modularity and maintainability of the page, making the entire front-end page structure clearer and easier to manage.

[0084] The embodiment of the present invention displays a static component with a specific function at a specified position of a front-end page, and ensures that a plug-in with an enabled function can be embedded inside the static component, thereby providing users with a richer and more flexible page interaction experience.

[0085] Optionally, after obtaining the data query result in step S103, the following steps are further included:

[0086] A data query result display area is created, and a function button is set on the display area, wherein the function button is used to send the data query result to the user.

[0087] The data query result display area can be a specific location on the page or a pop-up modal box. In the display area, the style and structure of the displayed data can be designed and laid out through HTML (Hypertext Markup Language) and CSS, so that users can clearly view the data content. Function buttons are set on the display area. The function buttons can be icons or text buttons for performing different operations, including function buttons for sending data query results to users. In addition, other function buttons can be added, such as exporting data, printing data, copying data, etc., to enhance customer service's ability to operate and use data. When designing function buttons, the position, style and function of the buttons can be made to meet the expectations and needs of customer service based on the customer service's usage habits and convenience. At the same time, the button functions should be set to be consistent with the actual operation, and can interact with the back-end system to realize the data sending and processing functions, improve the customer service experience, and enable customer service to use the queried data for subsequent operations more conveniently.

[0088] Optionally, step S101 obtains user consultation information corresponding to the data query request, including:

[0089] Parameter information of the user consultation information is parsed from the data query request, and the user consultation information is acquired according to the parameter information.

[0090] The parameter information of user consultation information includes user ID, query keywords, query time range, etc. By parsing the above parameter information, the specific content and scope of the user consultation information to be obtained can be determined; according to the parsed parameter information, the corresponding data query interface or database query statement can be used to obtain the required user consultation information. For example, the user's historical consultation records can be queried by user ID, or qualified consultation information can be queried by keywords, etc.

[0091] The embodiments of the present invention can effectively obtain user consultation information corresponding to data query requests, and provide the required data support for subsequent data processing and display, quickly and accurately obtain relevant information according to user needs, and improve system response speed and user experience.

[0092] According to a second aspect of the embodiment of the present invention, Figure 5 As shown, a data query device 500 is provided, comprising:

[0093] The acquisition module 501 is used to respond to the received data query request and acquire the user consultation information corresponding to the data query request;

[0094] A search module 502 is used to extract keywords from the user consultation information and, based on the extraction results, search for a target plug-in corresponding to the extraction results from a pre-configured plug-in list;

[0095] The query module 503 is used to use the target plug-in to perform data query according to the extraction result to obtain a data query result.

[0096] Optionally, the search module 502 is further used to:

[0097] The user consultation information is preprocessed; the preprocessing includes at least one of the following: text cleaning, missing value completion, and word form normalization.

[0098] Extract keywords from the preprocessed user consultation information based on the keyword extraction algorithm;

[0099] The keywords are screened to obtain the extraction results.

[0100] Optionally, the data query device 500 further includes a configuration module, and the configuration module is used to:

[0101] Performing function switch configuration on at least one predetermined plug-in to obtain a configuration result; wherein the function switch includes enabling and / or disabling the plug-in;

[0102] A plug-in list is generated based on the configuration result.

[0103] Optionally, the data query device 500 further includes an integration module, and the integration module is used to:

[0104] The plug-in list is integrated into the front-end page. After the front-end page is loaded, the plug-ins in the plug-in list can automatically register plug-ins through a registration mechanism and monitor data query operations.

[0105] Optionally, the configuration module is further used to:

[0106] Setting a static component at a specified position on the front-end page, wherein the specified position is determined by setting a top offset attribute, a left offset attribute, a right offset attribute, or a bottom offset attribute in a cascading style sheet;

[0107] The plug-in with the function switch enabled is embedded into the static component.

[0108] Optionally, the data query device 500 further includes a display module, and the display module is used to:

[0109] A data query result display area is created, and a function button is set on the display area, wherein the function button is used to send the data query result to the user.

[0110] Optionally, the acquisition module is further used for:

[0111] Parameter information of the user consultation information is parsed from the data query request, and the user consultation information is acquired according to the parameter information.

[0112] It should be noted that the specific implementation content of the data query device of the present invention has been described in detail in the data query method described above, so the repeated content will not be described again here.

[0113] According to a third aspect of an embodiment of the present invention, there is provided an electronic device, including:

[0114] one or more processors;

[0115] a storage device for storing one or more programs,

[0116] When the one or more programs are executed by the one or more processors, the one or more processors implement the method provided in the first aspect of the embodiment of the present invention.

[0117] According to a fourth aspect of an embodiment of the present invention, a computer-readable medium is provided, on which a computer program is stored, and when the program is executed by a processor, the method provided by the first aspect of the embodiment of the present invention is implemented.

[0118] Figure 6 An exemplary system architecture 600 is shown to which the data query method or data query device according to the embodiment of the present invention can be applied.

[0119] like Figure 6 As shown, system architecture 600 may include terminal devices 601, 602, 603, network 604 and server 605. Network 604 is used to provide a medium for communication links between terminal devices 601, 602, 603 and server 605. Network 604 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0120] The user can use the terminal devices 601, 602, 603 to interact with the server 605 through the network 604 to receive or send messages, etc. Various communication client applications can be installed on the terminal devices 601, 602, 603, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social platform software, etc. (only for example).

[0121] The terminal devices 601 , 602 , and 603 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop computers, and desktop computers, etc.

[0122] The server 605 may be a server that provides various services, such as a backend management server (only an example) that provides support for shopping websites browsed by users using the terminal devices 601, 602, and 603. The backend management server may analyze and process the received data such as the data query request, and feed back the processing result (such as the data query result - only an example) to the terminal device.

[0123] It should be noted that the data query method provided in the embodiment of the present invention is generally executed by the server 605 , and accordingly, the data query device is generally disposed in the server 605 .

[0124] It should be understood that Figure 6 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0125] Reference below Figure 7 , which shows a schematic diagram of the structure of a computer system 700 of a terminal device suitable for implementing an embodiment of the present invention. Figure 7 The terminal device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0126] like Figure 7 As shown, the computer system 700 includes a central processing unit (CPU) 701, which can execute various appropriate actions and processes according to a program stored in a read-only memory (ROM) 702 or a program loaded from a storage part 708 into a random access memory (RAM) 703. In the RAM 703, various programs and data required for the operation of the system 700 are also stored. The CPU 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0127] The following components are connected to the I / O interface 705: an input section 706 including a keyboard, a mouse, etc.; an output section 707 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 708 including a hard disk, etc.; and a communication section 709 including a network interface card such as a LAN card, a modem, etc. The communication section 709 runs a communication process via a network such as the Internet. A drive 710 is also connected to the I / O interface 705 as needed. A removable medium 711, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 710 as needed, so that a computer program read therefrom is installed into the storage section 708 as needed.

[0128] In particular, according to the embodiments disclosed in the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, the embodiments disclosed in the present invention include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program code for running the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 709, and / or installed from the removable medium 711. When the computer program is executed by the central processing unit (CPU) 701, the above-mentioned functions defined in the system of the present invention are executed.

[0129] It should be noted that the computer-readable medium shown in the present invention may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, device or device. In the present invention, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable program code. This propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0130] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, functions and operations of the system, method and computer program product according to various embodiments of the present invention. In this regard, each box in the flow chart or block diagram can represent a module, a program segment, or a part of a code, and the above-mentioned module, program segment, or a part of a code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually run basically in parallel, and they can sometimes run in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flow chart, and the combination of the boxes in the block diagram or flow chart can be implemented with a dedicated hardware-based system that runs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0131] The modules involved in the embodiments of the present invention may be implemented in software or hardware. The modules described may also be provided in a processor. For example, they may be described as follows: a processor includes an acquisition module, a search module, and a query module. The names of these modules do not, in some cases, constitute limitations on the modules themselves. For example, the acquisition module may also be described as a "module for responding to a received data query request and acquiring user consultation information corresponding to the data query request."

[0132] As another aspect, the present invention also provides a computer-readable medium, which may be included in the device described in the above embodiment; or it may exist independently without being assembled into the device. The above computer-readable medium carries one or more programs, and when the above one or more programs are executed by a device, the device includes: in response to a received data query request, obtaining user consultation information corresponding to the data query request; performing keyword extraction on the user consultation information, and based on the extraction result, finding the target plug-in corresponding to the extraction result from a pre-configured plug-in list; using the target plug-in to perform data query according to the extraction result to obtain the data query result.

[0133] The technical solution according to the embodiment of the present invention has the following advantages or beneficial effects: by responding to a received data query request, user consultation information corresponding to the data query request is obtained; keywords are extracted from the user consultation information, and based on the extraction result, a target plug-in corresponding to the extraction result is found from a pre-configured plug-in list; data query is performed according to the extraction result using the target plug-in to obtain a data query result; relevant data of the user consultation information can be automatically queried, and the query speed and efficiency are high.

[0134] The above specific implementations do not constitute a limitation on the protection scope of the present invention. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may occur depending on design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

[0135] It should be noted that the acquisition, storage and application of user personal information involved in the technical solution of the present disclosure are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

Claims

1. A data query method, characterized in that: include: In response to the received data query request, obtaining user consultation information corresponding to the data query request; Perform keyword extraction on the user inquiry information, and based on the extraction result, find a target plug-in corresponding to the extraction result from a pre-configured plug-in list; The target plug-in is used to perform data query according to the extraction result to obtain a data query result.

2. The method according to claim 1, characterized in that Extracting keywords from the user consultation information includes: The user consultation information is preprocessed; the preprocessing includes at least one of the following: text cleaning, missing value completion, and word form normalization. Extract keywords from the preprocessed user consultation information based on the keyword extraction algorithm; The keywords are screened to obtain the extraction results.

3. The method according to claim 1, characterized in that The pre-configured plug-in list is obtained by following the steps below: Performing function switch configuration on at least one predetermined plug-in to obtain a configuration result; wherein the function switch includes enabling and / or disabling the plug-in; A plug-in list is generated based on the configuration result.

4. The method according to claim 3, characterized in that After the plug-in list is generated based on the configuration result, the following is further included: The plug-in list is integrated into the front-end page. After the front-end page is loaded, the plug-ins in the plug-in list can automatically register plug-ins through a registration mechanism and monitor data query operations.

5. The method according to claim 3, characterized in that: The method further comprises: Setting a static component at a specified position on the front-end page, wherein the specified position is determined by setting a top offset attribute, a left offset attribute, a right offset attribute, or a bottom offset attribute in a cascading style sheet; The plug-in with the function switch enabled is embedded into the static component.

6. The method according to claim 1, characterized in that After obtaining the data query results, it also includes: A data query result display area is created, and a function button is set on the display area, wherein the function button is used to send the data query result to the user.

7. The method according to claim 1, characterized in that Obtaining user consultation information corresponding to the data query request, including: Parameter information of the user consultation information is parsed from the data query request, and the user consultation information is acquired according to the parameter information.

8. A data query device, characterized in that: include: An acquisition module, configured to, in response to a received data query request, acquire user consultation information corresponding to the data query request; A search module, used to extract keywords from the user consultation information, and based on the extraction results, search for a target plug-in corresponding to the extraction results from a pre-configured plug-in list; The query module is used to use the target plug-in to perform data query according to the extraction result to obtain a data query result.

9. An electronic device, characterized in that: include: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 7.

10. A computer readable medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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