Knowledge base automatic supplementing method, system and equipment and storage medium

Abstract

The invention discloses a knowledge base automatic supplement method, system and device and a storage medium, and relates to the technical field of knowledge bases. The method is applied to the knowledge base automatic supplement system. The system comprises a quick search module and a knowledge management module, and the method comprises the steps that when a search instruction of a user is recognized through the quick search module, search data to be supplemented are determined according to historical search data of the user, and search recommendation content is supplemented according to the search data to be supplemented; when a knowledge point importing instruction of a user is recognized through a knowledge management module, batch processing is performed on the received candidate knowledge point data to obtain target knowledge point data, and the target knowledge point data is imported into a target knowledge base to supplement the target knowledge base; and supplementing the target knowledge base according to the received candidate vocabulary entries when recognizing the vocabulary entry adding instruction through the knowledge management module. Through the technical scheme, the efficiency of automatically supplementing the knowledge base can be improved.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of computer technology, in particular to the field of knowledge base technology, and specifically to a method, system, device and storage medium for automatically supplementing a knowledge base. Background Art

[0002] With the development of the Internet, many companies will create their own knowledge bases to collect and organize the company's information and knowledge on a large scale, classify and save them according to certain methods, and provide corresponding retrieval methods. After a large amount of information and knowledge is entered into the knowledge base, after some processing, a large amount of implicit knowledge is encoded and digitized, and the information and knowledge are transformed from the original chaotic state into order, which facilitates the retrieval of information and knowledge.

[0003] At present, the way to add new business knowledge to the knowledge base is generally to add it regularly at a certain period. However, the appearance time of new knowledge that needs to be added to the knowledge base is often random. A large amount of new knowledge that needs to be added may appear in a short period of time, or no new knowledge may appear for a long time. Summary of the invention

[0004] The present application provides a knowledge base automatic supplement method, system, device and storage medium to improve the efficiency of knowledge base automatic supplement.

[0005] According to one aspect of the present application, a knowledge base automatic supplement method is provided, which is applied to a knowledge base automatic supplement system; the system includes a quick search module and a knowledge management module; the method includes:

[0006] When the quick search module recognizes the search instruction of the user, the search data to be supplemented is determined according to the historical search data of the user, and the search recommendation content is supplemented according to the search data to be supplemented;

[0007] When the knowledge management module recognizes the knowledge point import instruction of the user, batch processing is performed on the received candidate knowledge point data to obtain target knowledge point data, and the target knowledge point data is imported into the target knowledge base to supplement the target knowledge base;

[0008] When the knowledge management module identifies a new entry instruction, the target knowledge base is supplemented according to the received candidate entries.

[0009] According to another aspect of the present application, a knowledge base automatic supplement system is provided, the system comprising a quick search module and a knowledge management module;

[0010] The quick search module is used to determine the search data to be supplemented according to the historical search data of the user when recognizing the search instruction of the user, and supplement the search recommendation content according to the search data to be supplemented;

[0011] The knowledge management module is used to batch process the received candidate knowledge point data to obtain target knowledge point data when identifying the knowledge point import instruction of the user, and import the target knowledge point data into the target knowledge base to supplement the target knowledge base;

[0012] The knowledge management module is further configured to supplement the target knowledge base according to the received candidate entries when a new entry addition instruction is identified.

[0013] According to another aspect of the present application, an electronic device is provided, the electronic device comprising:

[0014] one or more processors;

[0015] A memory for storing one or more programs;

[0016] When the one or more programs are executed by the one or more processors, the one or more processors implement any one of the knowledge base automatic supplement methods provided in the embodiments of the present application.

[0017] According to another aspect of the present application, a computer-readable storage medium is provided, on which a computer program is stored. When the program is executed by a processor, any one of the knowledge base automatic supplement methods provided in the embodiments of the present application is implemented.

[0018] When the quick search module of this application recognizes the search instruction of the user, it determines the search data to be supplemented according to the historical search data of the user, and supplements the search recommendation content according to the search data to be supplemented; when the knowledge management module recognizes the knowledge point import instruction of the user, it batch processes the received candidate knowledge point data to obtain the target knowledge point data, and imports the target knowledge point data into the target knowledge base to supplement the target knowledge base; when the knowledge management module recognizes the new entry instruction, it supplements the target knowledge base according to the received candidate entries. The above technical scheme, by responding to the user's instructions in a timely manner, performs targeted processing on the search data, knowledge points and entries that need to be supplemented, and automatically supplements the qualified data into the target knowledge base, can improve the efficiency of automatic supplementation of the knowledge base while ensuring the accuracy of the supplemented data. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 is a flow chart of a method for automatically supplementing a knowledge base provided according to Embodiment 1 of the present application;

[0020] Figure 2 is a flow chart of a method for automatically supplementing a knowledge base provided according to Embodiment 2 of the present application;

[0021] Figure 3 is a structural diagram of a knowledge base automatic supplement system provided according to Embodiment 3 of the present application;

[0022] Figure 4 It is a structural schematic diagram of an electronic device that implements the knowledge base automatic supplement method of an embodiment of the present application. DETAILED DESCRIPTION

[0023] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present application.

[0024] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0025] In addition, it should be noted that in the technical solution of this application, the collection, storage, use, processing, transmission, provision and disclosure of relevant data such as historical search data and search data to be supplemented are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0026] Before further describing the present application in detail, the knowledge base system involved in the embodiments of the present invention is described:

[0027] The core functions of the knowledge base system of this application are the portal navigation module and the intelligent knowledge center module.

[0028] The portal navigation function includes portal system login, function module navigation, quick search, knowledge relationship map construction, home page content and other modules;

[0029] Quick search module, used to display the latest updates and popular contents in the encyclopedia and library through other contents on the homepage, including announcements, encyclopedia and library categories, entry recommendations, and what everyone is paying attention to;

[0030] The knowledge relationship graph construction module is used to view the relationship between various pieces of knowledge and provide users with a graphical and structured knowledge map, allowing users to easily query knowledge content;

[0031] The home page content module is used for other home page content including announcements, encyclopedia and library classifications, entry recommendations, what everyone is paying attention to, and the display of the latest updates and popular content in the encyclopedia and library.

[0032] The functions of the intelligent knowledge center include encyclopedia, library, data statistics, knowledge management and other modules;

[0033] The encyclopedia module is used to search and manage knowledge and terms based on the terms recommended by the system for query. It uses the knowledge graph to sort out the relationships between knowledge points, encyclopedia knowledge base operation status, popular encyclopedia knowledge searches, recently updated knowledge information that everyone is concerned about, personnel encyclopedia contributions and user latest dynamics through classification browsing;

[0034] The document library module is used to search and manage files. You can also browse related files by category, view the operation status of the document library, recommended files, hot search files, document library update content, document library contribution list, user dynamics, popular categories that everyone is concerned about, and map recommendations;

[0035] The data statistics module is used for report statistics of the intelligent knowledge center related data, including home page data statistics, user data, encyclopedia data, library data and search index analysis;

[0036] The knowledge management module is used to manage the relevant content related to encyclopedias, libraries, and data statistics in the knowledge base.

[0037] Embodiment 1

[0038] Figure 1 This is a flow chart of a knowledge base automatic supplement method provided according to the first embodiment of the present application. This embodiment is applicable to the situation of automatically supplementing the content in the knowledge base, which can be executed by a knowledge base automatic supplement system. The knowledge base automatic supplement system can be implemented in the form of hardware and / or software. The knowledge base automatic supplement system includes a quick search module and a knowledge management module, which can be configured in a computer device, such as a server. Figure 1 As shown, the method includes:

[0039] S110. When the quick search module recognizes the search instruction of the user, it determines the search data to be supplemented according to the historical search data of the user, and supplements the search recommendation content according to the search data to be supplemented.

[0040] Among them, the quick search module refers to the component or engine in the knowledge base that is used to instantly process the user's search request. The user refers to the user who is currently using the knowledge base. The search instruction refers to the instruction that the user triggers the start of the quick search module. Exemplarily, the instruction can be a mouse click on the text input area of ​​the quick search area. Historical search data refers to previous search records and behavior data, which may include the user's search volume for knowledge points, terms, etc.; specifically, historical search data may include historical term search data, historical knowledge point search data, and historical document search data. The search data to be supplemented refers to the relevant search data that needs to be supplemented into the knowledge base system, which may include popular knowledge points, popular terms, popular documents, etc. Specifically, the search data to be supplemented may include search terms to be supplemented, knowledge points to be supplemented, and search documents to be supplemented. Search recommendation content refers to the recommended content displayed to the user when the user uses the quick search module.

[0041] Optionally, determining the search data to be supplemented based on the user's historical search data can be by sorting the search volume of each term in the historical term search data, and determining a preset number of terms ranked first as search terms to be supplemented; sorting the search volume of each knowledge point in the historical knowledge point search data, and determining a preset number of knowledge points ranked first as search knowledge points to be supplemented; sorting the search volume of each document in the historical document search data, and determining a preset number of documents ranked first as search documents to be supplemented.

[0042] Among them, the search terms to be supplemented refer to the terms with high search volume by users. The search knowledge points to be supplemented refer to the knowledge points with high search volume by users. The search documents to be supplemented refer to the documents with high search volume by users. The preset number is artificially pre-set based on actual conditions or experience values.

[0043] Exemplarily, the search volume of each term in the historical term search data is sorted, and the term with the highest search volume is determined as the search term to be supplemented; the search volume of each knowledge point in the historical knowledge point search data is sorted, and the knowledge point with the highest search volume is determined as the search knowledge point to be supplemented; the search volume of each document in the historical document search data is sorted, and the document with the highest search volume is determined as the search document to be supplemented.

[0044] S120. When the knowledge management module recognizes the knowledge point import instruction of the user, the received candidate knowledge point data is batch processed to obtain target knowledge point data, and the target knowledge point data is imported into the target knowledge base to supplement the target knowledge base.

[0045] Among them, the knowledge management module refers to the system component or software function in the knowledge base system, which is used to manage and process the import, update and maintenance of knowledge points. The knowledge point import instruction refers to the instruction issued by the user, requesting the import of new knowledge point data into the system. Candidate knowledge point data refers to the knowledge point data to be processed, which may come from different sources and need to be screened and sorted; specifically, the candidate knowledge point data may include candidate knowledge points and candidate documents; illustratively, the candidate knowledge point data can be uploaded by the user. Target knowledge point data refers to the final knowledge point data that has been processed and verified, and these data are ready to be imported into the knowledge base; specifically, the target knowledge point data may include target knowledge points and target documents.

[0046] Optionally, the received candidate knowledge point data may be processed in batches to obtain target knowledge point data by performing feasibility checks on the candidate knowledge points and format checks on the structural elements of the candidate documents; the structural elements include document formats, document attributes and document titles; the candidate knowledge points that pass the feasibility check are determined as target knowledge points, and the candidate documents that pass the format check are determined as target documents.

[0047] Among them, candidate knowledge points refer to knowledge data to be evaluated, and it has not yet been determined whether they meet the requirements or can be included in the knowledge base. Feasibility verification refers to the verification of candidate knowledge points to ensure that their content, accuracy and relevance meet the standards, such as whether there are indecent words, whether there are repeated knowledge points, whether the knowledge points are correct, etc. Structural elements refer to the key components of a document, which can include at least one of the document format, document attributes and document title. Format verification refers to checking the structural elements of candidate documents to ensure that they meet the predetermined format and specifications, such as whether the document title is repeated, whether the document format is correct, whether the document attributes meet the requirements, etc. Target knowledge points refer to knowledge point data that have passed feasibility verification and are determined to be the data that will be finally included in the knowledge base. Target documents refer to documents that have passed format verification, are confirmed to meet the standards and are ready for further storage.

[0048] S130. When a new entry instruction is identified through the knowledge management module, the target knowledge base is supplemented according to the received candidate entries.

[0049] Among them, the entry addition instruction refers to the instruction issued by the user to add a new entry or knowledge point to the knowledge base. The candidate entry refers to the entry to be added to the knowledge base, which needs to be processed or verified to determine whether it meets the requirements. The target knowledge base refers to the database or system used to store and manage knowledge points, which contains all adopted and verified knowledge data.

[0050] Specifically, when the knowledge management module recognizes an instruction to add a new entry, it checks the candidate name of the received candidate entry for consistency with the entry name currently existing in the target knowledge base; in the event of a duplicate entry name, it determines that the candidate entry does not meet the standards and does not need to be added to the target knowledge base; in the event of a duplicate entry name, it determines that the candidate entry meets the standards and is added to the target knowledge base.

[0051] In the embodiment of the present application, when the quick search module recognizes the search instruction of the user, it determines the search data to be supplemented according to the historical search data of the user, and supplements the search recommendation content according to the search data to be supplemented; when the knowledge management module recognizes the knowledge point import instruction of the user, it batch processes the received candidate knowledge point data to obtain the target knowledge point data, and imports the target knowledge point data into the target knowledge base to supplement the target knowledge base; when the knowledge management module recognizes the new entry instruction, it supplements the target knowledge base according to the received candidate entries. The above technical scheme, by responding to the user's instructions in a timely manner, performs targeted processing on the search data, knowledge points and entries that need to be supplemented, and automatically supplements the qualified data into the target knowledge base, can improve the efficiency of automatic supplementation of the knowledge base while ensuring the accuracy of the supplemented data.

[0052] Embodiment 2

[0053] Figure 2 This is a flow chart of a method for automatically supplementing a knowledge base provided in accordance with the second embodiment of the present application. Based on the technical solutions of the above embodiments, this embodiment refines "supplementing the target knowledge base based on the received candidate terms" into "conducting a consistency check between the received candidate terms and the current terms in the target knowledge base, and determining the candidate terms that fail the consistency check as the target terms; establishing an association relationship between the target terms and the current terms based on the target knowledge attributes and the target hierarchical order of the target terms, so as to supplement the target knowledge base". It should be noted that for the parts not described in detail in the embodiments of the present application, please refer to the relevant statements of other embodiments. Figure 2 As shown, the method includes:

[0054] S210. When the quick search module recognizes the search instruction of the user, it determines the search data to be supplemented according to the historical search data of the user, and supplements the search recommendation content according to the search data to be supplemented.

[0055] S220. When the knowledge management module recognizes the knowledge point import instruction of the user, the received candidate knowledge point data is batch processed to obtain the target knowledge point data, and the target knowledge point data is imported into the target knowledge base to supplement the target knowledge base.

[0056] S230. When a new entry instruction is identified through the knowledge management module, the received candidate entry is checked for consistency with the current entry in the target knowledge base, and the candidate entry that fails the consistency check is determined as the target entry.

[0057] Among them, consistency check refers to comparing the candidate terms with existing terms in the target knowledge base to check whether their content is consistent with the existing terms; illustratively, it can be comparing the names between the terms.

[0058] It is understandable that by performing consistency check on the candidate terms and the current terms, repeated supplementation of the same terms can be avoided, resource waste can be avoided, and the efficiency of automatic supplementation can be improved.

[0059] S240. Establishing an association relationship between the target term and the current term through the knowledge management module according to the target knowledge attribute and the target hierarchical order of the target term, so as to supplement the target knowledge base.

[0060] Among them, the target knowledge attribute refers to the characteristics or features of the target term, including definition, category, purpose, etc. The target hierarchy refers to the hierarchical relationship of the target term in the knowledge base. The upper-level term is a broader concept, and the lower-level term is a more specific concept. The hierarchy relationship helps to establish the logical and structural association between terms. The association relationship refers to the relationship between the target term and the current term to ensure that the information in the knowledge base is comprehensive and well-structured; specifically, the association relationship includes attribute association relationship and rank association relationship.

[0061] Optionally, the knowledge management module determines the current term whose candidate term attributes are consistent with the target knowledge attributes as the first associated term, and establishes an attribute association relationship between the first associated term and the target term; determines the current term whose candidate upper and lower positions are consistent with the target upper and lower positions as the second associated term, and establishes a position association relationship between the second associated term and the target term.

[0062] Among them, the attribute association relationship refers to the relationship established between the first associated term and the target term, reflecting their consistency and similarity in attributes. The position association relationship refers to the relationship established between the second associated term and the target term, reflecting their consistency in level or position.

[0063] It can be understood that by establishing attribute association relationships and rank association relationships, the coherence of the structure and content of the knowledge base can be enhanced.

[0064] In the embodiment of the present application, when the quick search module recognizes the search instruction of the user, it determines the search data to be supplemented according to the historical search data of the user, and supplements the search recommendation content according to the search data to be supplemented; when the knowledge management module recognizes the knowledge point import instruction of the user, it batch processes the received candidate knowledge point data to obtain the target knowledge point data, and imports the target knowledge point data into the target knowledge base to supplement the target knowledge base; when the knowledge management module recognizes the new entry instruction, it supplements the target knowledge base according to the received candidate entries. The above technical scheme, by responding to the user's instructions in a timely manner, performs targeted processing on the search data, knowledge points and entries that need to be supplemented, and automatically supplements the qualified data into the target knowledge base, can improve the efficiency of automatic supplementation of the knowledge base while ensuring the accuracy of the supplemented data.

[0065] Embodiment 3

[0066] Figure 3 This is a schematic diagram of the structure of a knowledge base automatic supplement system provided according to the third embodiment of the present application, which can be applied to the situation of automatically supplementing the content in the knowledge base. The knowledge base automatic supplement system can be implemented in the form of hardware and / or software. The knowledge base automatic supplement system can be configured in a computer device, such as a server. Figure 3 As shown, the system includes a quick search module 310 and a knowledge management module 320;

[0067] The quick search module 310 is used to determine the search data to be supplemented according to the historical search data of the user when recognizing the search instruction of the user, and supplement the search recommendation content according to the search data to be supplemented;

[0068] The knowledge management module 320 is used to batch process the received candidate knowledge point data when identifying the knowledge point import instruction of the user, obtain the target knowledge point data, and import the target knowledge point data into the target knowledge base to supplement the target knowledge base;

[0069] The knowledge management module 320 is also used to supplement the target knowledge base according to the received candidate terms when a new term addition instruction is identified.

[0070] In the embodiment of the present application, when the quick search module recognizes the search instruction of the user, it determines the search data to be supplemented according to the historical search data of the user, and supplements the search recommendation content according to the search data to be supplemented; when the knowledge management module recognizes the knowledge point import instruction of the user, it batch processes the received candidate knowledge point data to obtain the target knowledge point data, and imports the target knowledge point data into the target knowledge base to supplement the target knowledge base; when the knowledge management module recognizes the new entry instruction, it supplements the target knowledge base according to the received candidate entries. The above technical scheme, by responding to the user's instructions in a timely manner, performs targeted processing on the search data, knowledge points and entries that need to be supplemented, and automatically supplements the qualified data into the target knowledge base, can improve the efficiency of automatic supplementation of the knowledge base while ensuring the accuracy of the supplemented data.

[0071] Optionally, the historical search data includes historical term search data, historical knowledge point search data and historical document search data; the search data to be supplemented includes search terms to be supplemented, search knowledge points to be supplemented and search documents to be supplemented.

[0072] Optionally, the quick search module 310 is specifically used for:

[0073] Sorting the search volume of each term in the historical term search data, and determining a preset number of terms ranked first as the search terms to be supplemented;

[0074] Sorting the search volume of each knowledge point in the historical knowledge point search data, and determining a preset number of knowledge points ranked first as knowledge points to be supplemented;

[0075] The search volume of each document in the historical document search data is sorted, and a preset number of documents ranked first are determined as the search documents to be supplemented.

[0076] Optionally, the candidate knowledge point data includes candidate knowledge points and candidate documents; the target knowledge point data includes target knowledge points and target documents; accordingly, the knowledge management module 320 is specifically used to:

[0077] When the knowledge point import instruction of the user is identified, the feasibility of the candidate knowledge point is checked, and the format of the structural elements of the candidate document is checked; the structural elements include the document format, document attributes and document title;

[0078] The candidate knowledge points that pass the feasibility check are determined as target knowledge points, and the candidate documents that pass the format check are determined as target documents.

[0079] Optionally, the knowledge management module 320 includes:

[0080] The term determination unit is used to perform consistency check between the received candidate terms and the current terms in the target knowledge base, and determine the candidate terms that fail the consistency check as target terms;

[0081] The relationship establishment unit is used to establish an association relationship between the target term and the current term according to the target knowledge attribute and the target upper and lower order of the target term, so as to supplement the target knowledge base.

[0082] Optionally, the association relationship includes an attribute association relationship and a position association relationship; accordingly, the relationship establishment unit is specifically used to:

[0083] Determine the current entry whose attributes of the candidate entry are consistent with the target knowledge attributes as the first associated entry, and establish an attribute association relationship between the first associated entry and the target entry;

[0084] The current term whose candidate upper and lower rank is consistent with the target upper and lower rank is determined as the second associated term, and a rank association relationship is established between the second associated term and the target term.

[0085] The knowledge base automatic supplement system provided in the embodiments of the present application can execute the knowledge base automatic supplement method provided in any embodiment of the present application, and has the corresponding functional modules and beneficial effects for executing each knowledge base automatic supplement method.

[0086] Embodiment 4

[0087] Figure 4 It is a structural diagram of an electronic device 410 that implements the knowledge base automatic supplement method of an embodiment of the present application. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are only examples and are not intended to limit the implementation of the present application described and / or required herein.

[0088] like Figure 4As shown, the electronic device 410 includes at least one processor 411, and a memory connected to the at least one processor 411 in communication, such as a read-only memory (ROM) 412, a random access memory (RAM) 413, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 411 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 412 or the computer program loaded from the storage unit 418 to the random access memory (RAM) 413. In RAM413, various programs and data required for the operation of the electronic device 410 can also be stored. The processor 411, ROM412 and RAM413 are connected to each other via a bus 414. An input / output (I / O) interface 415 is also connected to the bus 414.

[0089] Multiple components in the electronic device 410 are connected to the I / O interface 415, including: an input unit 416, such as a keyboard, a mouse, etc.; an output unit 417, such as various types of displays, speakers, etc.; a storage unit 418, such as a disk, an optical disk, etc.; and a communication unit 419, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 419 allows the electronic device 410 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0090] The processor 411 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 411 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The processor 411 executes the various methods and processes described above, such as the knowledge base automatic supplement method.

[0091] In some embodiments, the knowledge base automatic supplement method can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 418. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 410 via the ROM 412 and / or the communication unit 419. When the computer program is loaded into the RAM 413 and executed by the processor 411, one or more steps of the knowledge base automatic supplement method described above can be performed. Alternatively, in other embodiments, the processor 411 can be configured as a knowledge base automatic supplement method in any other appropriate manner (e.g., by means of firmware).

[0092] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0093] The computer programs for implementing the methods of the present application may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable knowledge base automatic replenishment device, so that when the computer program is executed by the processor, the functions / operations specified in the flow chart and / or block diagram are implemented. The computer program may be executed entirely on the machine, partially on the machine, partially on the machine as a stand-alone software package and partially on a remote machine, or entirely on a remote machine or server.

[0094] In the context of the present application, a computer readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, device or equipment. A computer readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, a computer readable storage medium may be a machine readable signal medium. A more specific example of a machine readable storage medium may include an electrical connection based on one or more lines, 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 foregoing.

[0095] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0096] The systems and techniques described herein may be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0097] A computing system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The client and server relationship is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services.

[0098] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this application can be executed in parallel, sequentially or in different orders, as long as the expected results of the technical solution of this application can be achieved, and this document is not limited here.

[0099] The above specific implementations do not constitute a limitation on the protection scope of this application. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.

Claims

1. A method for automatically supplementing a knowledge base, characterized in that: Applied to a knowledge base automatic supplement system; the system includes a quick search module and a knowledge management module; the method includes: When the quick search module recognizes the search instruction of the user, the search data to be supplemented is determined according to the historical search data of the user, and the search recommendation content is supplemented according to the search data to be supplemented; When the knowledge management module recognizes the knowledge point import instruction of the user, batch processing is performed on the received candidate knowledge point data to obtain target knowledge point data, and the target knowledge point data is imported into the target knowledge base to supplement the target knowledge base; When the knowledge management module identifies a new entry instruction, the target knowledge base is supplemented according to the received candidate entries.

2. The method according to claim 1, characterized in that The historical search data includes historical term search data, historical knowledge point search data and historical document search data; the to-be-supplemented search data includes to-be-supplemented search terms, to-be-supplemented search knowledge points and to-be-supplemented search documents.

3. The method according to claim 2, characterized in that Determine the search data to be supplemented based on the historical search data of the user, including: Sorting the search volume of each term in the historical term search data, and determining a preset number of terms in the top order as the search terms to be supplemented; Sorting the search volume of each knowledge point in the historical knowledge point search data, and determining a preset number of knowledge points ranked first as knowledge points to be supplemented for search; The search volume of each document in the historical document search data is sorted, and a preset number of documents ranked first are determined as the search documents to be supplemented.

4. The method according to claim 1, characterized in that: The candidate knowledge point data includes candidate knowledge points and candidate documents; the target knowledge point data includes target knowledge points and target documents; accordingly, when the knowledge management module identifies the knowledge point import instruction of the user, batch processing is performed on the received candidate knowledge point data to obtain the target knowledge point data, including: When the knowledge management module identifies the knowledge point import instruction of the user, the feasibility check of the candidate knowledge point is performed, and the format check of the structural elements of the candidate document is performed; the structural elements include document format, document attributes and document title; The candidate knowledge points that pass the feasibility check are determined as target knowledge points, and the candidate documents that pass the format check are determined as target documents.

5. The method according to claim 1, characterized in that The target knowledge base is supplemented according to the received candidate terms, including: Performing a consistency check between the received candidate terms and the current terms in the target knowledge base, and determining the candidate terms that fail the consistency check as target terms; According to the target knowledge attribute and the target upper and lower order of the target term, an association relationship between the target term and the current term is established to supplement the target knowledge base.

6. The method according to claim 5, characterized in that The association relationship includes an attribute association relationship and a rank association relationship; accordingly, according to the target knowledge attribute and the target upper and lower ranks of the target entry, an association relationship between the target entry and the current entry is established, including: Determine the current entry whose candidate entry attribute is consistent with the target knowledge attribute as the first associated entry, and establish an attribute association relationship between the first associated entry and the target entry; The current term whose candidate upper and lower rank is consistent with the target upper and lower rank is determined as the second associated term, and a rank association relationship is established between the second associated term and the target term.

7. A knowledge base automatic supplement system, characterized in that: The system includes a quick search module and a knowledge management module; The quick search module is used to determine the search data to be supplemented according to the historical search data of the user when recognizing the search instruction of the user, and supplement the search recommendation content according to the search data to be supplemented; The knowledge management module is used to batch process the received candidate knowledge point data to obtain target knowledge point data when identifying the knowledge point import instruction of the user, and import the target knowledge point data into the target knowledge base to supplement the target knowledge base; The knowledge management module is further configured to supplement the target knowledge base according to the received candidate entries when a new entry addition instruction is identified.

8. An electronic device, characterized in that: include: one or more processors; A memory 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 knowledge base automatic supplement method as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for automatically supplementing a knowledge base as described in any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the computer program implements the method for automatically supplementing a knowledge base according to any one of claims 1 to 6.

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