Data recommendation method, device and equipment, readable storage medium and program product
By analyzing the work log of the automatic control engineer to obtain the tag collection and matching the knowledge base screening tools and data, the problem of low manual search efficiency of the automatic control engineer is solved, and efficient and accurate information recommendation is achieved.
Patent Information
- Application Number
- CN202510436698.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-04-09
- Publication Date
- 2025-08-12
AI Technical Summary
When solving projects, self-control engineers need to manually search tools and information, resulting in low efficiency and poor timeliness, and may miss key technology developments and solutions.
By responding to trigger operations, obtaining the contract number of the project, parsing the work log to obtain the tag collection, matching the knowledge base, filtering and displaying relevant information and tools based on recommendation priorities.
It improves the work efficiency and accuracy of information acquisition of self-control engineers, and supports project management and technical selection decisions.
Smart Images
Figure CN120470037A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of data processing technology, and in particular to a data recommendation method, apparatus, computer equipment, computer-readable storage medium, and computer program product. Background Art
[0002] With the development of computer technology, intelligent recommendation technologies for big data have emerged. In industrial production, automation engineers need to handle different work nodes and projects across multiple industries. They are responsible for managing and implementing complex automated control systems that impact various sectors, from manufacturing to energy.
[0003] In traditional technology, when solving specific problems or projects, automatic control engineers need to manually search for relevant tools, materials and the latest technologies to complete different work tasks.
[0004] However, due to the complexity and rapid development of the industry, this manual search method is inefficient and time-sensitive, causing engineers to miss key technological developments and solutions. Summary of the Invention
[0005] Based on this, it is necessary to provide a data recommendation method, device, computer equipment, computer-readable storage medium and computer program product that can improve the work efficiency and timeliness of automatic control engineers in response to the above technical problems.
[0006] In a first aspect, the present application provides a data recommendation method, the method comprising:
[0007] responding to a trigger action on a target item;
[0008] According to the trigger operation, obtaining the contract number associated with the target project, and reading the work log corresponding to the target project based on the contract number;
[0009] Parse the work log corresponding to the target project to obtain a tag set for the target project;
[0010] Matching the tag set of the target project with the knowledge tags in the target knowledge base to search for materials and tools associated with the target project;
[0011] Based on a preset recommendation priority, select target materials and target tools from the materials and tools associated with the target project;
[0012] The target information and the target tool are displayed.
[0013] In one embodiment, parsing the work log corresponding to the target project to obtain a tag set of the target project includes:
[0014] Perform word segmentation extraction on the work log corresponding to the target project through a word segmenter to obtain several word segmentation results;
[0015] The word segmentation result is verified to obtain labels of several target items, and the labels of all the target items constitute a label set of the target items.
[0016] In one embodiment, the step of selecting target materials and target tools from the materials and tools associated with the target project based on a preset recommendation priority includes:
[0017] Filter candidate materials and candidate tools from the materials and tools associated with the target project according to the number of views and / or update time;
[0018] Arrange the candidate materials and the candidate tools in descending order according to the number of views and / or update time;
[0019] The candidate materials and the candidate tools ranked in the top N are used as target materials and target tools; wherein N is a natural number greater than 0.
[0020] In one embodiment, before responding to the triggering operation on the target item, the method further includes:
[0021] Build a target knowledge base based on the data files, question-and-answer knowledge, application tools, and application tool manuals that automatic control engineers need to use during their work;
[0022] Establishing a database table corresponding to the target knowledge base; the information in the database table includes: field name, type, and remarks;
[0023] Establish a tag library based on industry, product, and project nodes;
[0024] A tag library table corresponding to the tag library is established; the information in the tag library table includes: field name, type, and remarks.
[0025] In one embodiment, the method further comprises:
[0026] storing the updated knowledge in the target knowledge base, and / or,
[0027] The work log submitted by the automatic control engineer is parsed, and a storage table is generated based on the parsing result, and the storage table is stored in the target knowledge base; the information in the storage table includes: field name, type, and remarks.
[0028] In one embodiment, storing the updated knowledge in the target knowledge base includes:
[0029] Extract the updated knowledge through the word segmenter to obtain a word segmentation set;
[0030] Perform intersection matching on the word segmentation set and the tag library to obtain an intersection result;
[0031] After verifying the intersection result, a label set corresponding to the updated knowledge is obtained;
[0032] The tag set corresponding to the updated knowledge is stored in the target knowledge base.
[0033] In a second aspect, the present application further provides a data recommendation device, comprising:
[0034] A receiving module, configured to respond to a trigger operation on a target item;
[0035] an acquisition module, configured to acquire the contract number associated with the target project according to the trigger operation, and read the work log corresponding to the target project based on the contract number;
[0036] A parsing module, configured to parse the work log corresponding to the target project to obtain a tag set of the target project;
[0037] A matching module, configured to match the tag set of the target project with the knowledge tags in the target knowledge base, and search for materials and tools associated with the target project;
[0038] A screening module, configured to screen target materials and target tools from the materials and tools associated with the target project based on a preset recommendation priority;
[0039] The display module is used to display the target data and the target tool.
[0040] In a third aspect, the present application further provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:
[0041] responding to a trigger action on a target item;
[0042] According to the trigger operation, obtaining the contract number associated with the target project, and reading the work log corresponding to the target project based on the contract number;
[0043] Parse the work log corresponding to the target project to obtain a tag set for the target project;
[0044] Matching the tag set of the target project with the knowledge tags in the target knowledge base to search for materials and tools associated with the target project;
[0045] Based on a preset recommendation priority, select target materials and target tools from the materials and tools associated with the target project;
[0046] The target information and the target tool are displayed.
[0047] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the following steps are implemented:
[0048] responding to a trigger action on a target item;
[0049] According to the trigger operation, obtaining the contract number associated with the target project, and reading the work log corresponding to the target project based on the contract number;
[0050] Parse the work log corresponding to the target project to obtain a tag set for the target project;
[0051] Matching the tag set of the target project with the knowledge tags in the target knowledge base to search for materials and tools associated with the target project;
[0052] Based on a preset recommendation priority, select target materials and target tools from the materials and tools associated with the target project;
[0053] The target information and the target tool are displayed.
[0054] In a fifth aspect, the present application further provides a computer program product, comprising a computer program, which, when executed by a processor, implements the following steps:
[0055] responding to a trigger action on a target item;
[0056] According to the trigger operation, obtaining the contract number associated with the target project, and reading the work log corresponding to the target project based on the contract number;
[0057] Parse the work log corresponding to the target project to obtain a tag set for the target project;
[0058] Matching the tag set of the target project with the knowledge tags in the target knowledge base to search for materials and tools associated with the target project;
[0059] Based on a preset recommendation priority, select target materials and target tools from the materials and tools associated with the target project;
[0060] The target information and the target tool are displayed.
[0061] The above-mentioned data recommendation method, apparatus, computer equipment, computer-readable storage medium and computer program product respond to a trigger operation for a target project; according to the trigger operation, obtain the contract number associated with the target project, and read the work log corresponding to the target project based on the contract number; parse the work log corresponding to the target project to obtain a tag set for the target project; match the tag set of the target project with the knowledge tags in the target knowledge base, and search for materials and tools associated with the target project; based on a preset recommendation priority, filter out target materials and target tools from the materials and tools associated with the target project; and display the target materials and target tools. This can reduce the time for automatic control engineers to search for target project-related materials and tools, improve the accuracy and efficiency of recommended data, and provide good support for automatic control engineers' decision-making in project management, technology selection and solution design. BRIEF DESCRIPTION OF THE DRAWINGS
[0062] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments of the present application or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying any creative work.
[0063] Figure 1 Schematic diagram of a flow chart of a data recommendation method in one embodiment;
[0064] Figure 2 A schematic diagram illustrating the principle of storing knowledge in a database in one embodiment;
[0065] Figure 3 Schematic diagram of the overall workflow of a data recommendation method in one embodiment. DETAILED DESCRIPTION
[0066] In order to make the purpose, technical solutions and advantages of this application more clearly understood, the present application is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application.
[0067] In order to facilitate the understanding of the technical solutions in the embodiments of the present application, a brief explanation of the professional terms that may appear in the embodiments of the present application is first made:
[0068] Smart Recommendations: A system function based on algorithms and user behavior analysis, designed to predict user interests and needs, thereby providing personalized suggestions or recommended content.
[0069] Big Data refers to large, complex data sets that are difficult to process with traditional data processing tools. These data typically have three key characteristics: volume, variety, and high processing speed.
[0070] Industry Database: stores industry classifications, such as petrochemicals, pharmaceuticals, and nuclear power.
[0071] Project Node Database: stores project node categories, such as project team establishment, factory delivery, and site opening.
[0072] Product Database: stores company product categories, such as JX-300XP, OMC, and ECS-700.
[0073] For example, the embodiment of the present application aims to provide a data recommendation method to improve the work efficiency and accuracy of automatic control engineers. Figure 1 As shown, the method in the embodiment of the present application may include the following steps:
[0074] S101, responding to a triggering operation on a target item.
[0075] The embodiment of the present application can be applied to a server or a user terminal. When the method is applied to a server, an automatic control engineer can send a trigger operation for a target project to the server through a display interface provided by the user terminal. When the method is applied to a user terminal, the user terminal can respond to a trigger operation for a target project on a display interface, and then perform a subsequent series of processing steps. Wherein, the trigger operation can be that the automatic control engineer opens a project in a project management tool (for example, single-clicking or double-clicking a project control).
[0076] S102: According to the triggering operation, the contract number associated with the target project is obtained, and the work log corresponding to the target project is read based on the contract number.
[0077] In an embodiment of the present application, after receiving a trigger operation for a target project, the background automatically obtains the contract number associated with the target project and reads the work log corresponding to the target project based on the contract number.
[0078] S103: Parse the work log corresponding to the target project to obtain a tag set of the target project.
[0079] Exemplarily, the work log corresponding to the target project can be segmented and extracted by a word segmenter to obtain several segmentation results; the segmentation results are verified to obtain several labels of the target projects, and all the labels of the target projects constitute the label set of the target project.
[0080] For example, a tag set may be extracted from the work log by a word segmenter, for example: (medicine, FAT test, ECS-700, JX-300XP).
[0081] This embodiment adopts a tag association mechanism, that is, each document, question and answer, and tool is associated with a tag of the corresponding industry, project node, and product to ensure accurate classification and retrieval of information.
[0082] S104: Match the tag set of the target project with the knowledge tags in the target knowledge base, and search for materials and tools associated with the target project.
[0083] In the embodiment of the present application, a tag-by-tag comparison method or an intersection matching method can be used to obtain the data and tools associated with the target project.
[0084] The target knowledge base contains multi-dimensional information, such as industry library, project node library, product library, and knowledge library, which can effectively manage and associate various information resources.
[0085] S105 , based on the preset recommendation priority, select target materials and target tools from the materials and tools associated with the target project.
[0086] Exemplarily, candidate materials and candidate tools can be screened out from the materials and tools associated with the target project according to the number of views and / or update time; the candidate materials and candidate tools can be sorted in descending order according to the number of views and / or update time; the candidate materials and candidate tools ranked in the top N are used as target materials and target tools; wherein N is a natural number greater than 0.
[0087] S106, displaying target information and target tools.
[0088] In this embodiment of the application, tags can be matched with the knowledge tags of the existing knowledge base based on the known tag set, and sorted in descending order according to the number of views and update time, thereby realizing intelligent push of the knowledge base. Frequently viewed and recently updated materials and tools will be pushed to the automation engineers first to ensure the relevance and timeliness of the information.
[0089] This embodiment effectively integrates and manages multiple information resources, improves the efficiency and operability of engineering project management, and has significant advantages in information screening and push, providing more convenient and effective work support for automatic control engineers.
[0090] In an optional implementation, before executing step S101, the following steps may be further included:
[0091] Step A1: Build a target knowledge base based on the data files, question-and-answer knowledge, application tools, and instruction manuals of application tools that are needed by automatic control engineers during their work.
[0092] Step A2: Create a database table corresponding to the target knowledge base.
[0093] Illustratively, the structure of the database table is shown in Table 1, which may include: field name, type, and remarks.
[0094] Table 1
[0095] Field Name type Remark Title Varchar(255) Knowledge Title Content Text Knowledge Content Tags Array Tag Collection
[0096] Among them, Title represents the knowledge title, Content represents the knowledge content, Tags represents the tag set, Varchar(255) represents a variable-length string (storing up to 255 characters), Text represents text, and Array represents an array.
[0097] Step A3: Establish a tag library based on industry, product, and project nodes.
[0098] Step A4: Create a tag library table corresponding to the tag library.
[0099] Exemplarily, the table structure of the tag library is shown in Table 2. The information in the tag library table includes: field name, type, and remarks.
[0100] Table 2
[0101] Field Name type Remark Name Varchar(255) Tag Name Type Varcahr(255) Tag Type
[0102] Among them, Name represents the tag name, Type represents the tag type, and Varchar(255) represents a variable-length character string (can store up to 255 characters).
[0103] In another optional embodiment, the above method may further include the following steps:
[0104] Step B1: store the updated knowledge into the target knowledge base.
[0105] For example, Figure 2As shown, a schematic diagram illustrating the principle of storing knowledge in a database is provided. First, the updated knowledge is extracted through a word segmenter to obtain a word segmentation set; the word segmentation set is intersection-matched with the label library to obtain an intersection result; after verifying the intersection result, the label set corresponding to the updated knowledge is obtained; finally, the label set corresponding to the updated knowledge is stored in the target knowledge database.
[0106] In this embodiment, when each piece of knowledge is stored in the knowledge base, the word segmenter is first used to extract the word segments, and the word segmentation set is intersection-matched with the preset tag library. The intersection result is manually verified and adjusted before being stored in the knowledge base together with the knowledge, thereby ensuring accurate classification and retrieval of information.
[0107] In another optional embodiment, the above method may further include the following steps:
[0108] Step C1: parse the work log submitted by the automatic control engineer, generate a storage table based on the parsing result, and store the storage table in the target knowledge base; the information in the storage table includes: field name, type, and remarks.
[0109] In the embodiment of the present application, the automatic control engineer needs to submit a work log every day to record the work content, which includes the projects participated in and the nodes where the projects are located, as well as the products used in the projects and the industries in which they are located.
[0110] Based on the same principle as above, products, projects, project nodes, and industries can be extracted from work content as a label set through the word segmentation algorithm.
[0111] For example, the storage table structure is shown in Table 3.
[0112] Table 3
[0113] Field Name type Remark <![CDATA[Numbe r ]]> <![CDATA[Varcha r (255)]]> Employee ID Content Text Job Description CreateTime Timestamp Creation time Tags Array Tag Collection <![CDATA[Contract no ]]> <![CDATA[Varcha r (255)]]> Associated project contract number
[0114] Among them, Numbe r Indicates employee ID, Content indicates work content, CreateTime e Indicates creation time, Tags indicates a tag set, Contract_no indicates the contract number of the associated project, Varchar(255) indicates a variable-length string (storing up to 255 characters), Text indicates text, Timestamp indicates a timestamp, and Array indicates an array.
[0115] This embodiment manages engineers' work logs, enabling real-time updates of project information and supporting intelligent information push and management. Based on project information and work logs, highly relevant and timely materials and tools can be intelligently pushed, improving engineers' work efficiency and the accuracy of information searches.
[0116] For example, Figure 3 As shown, a schematic diagram of the overall workflow of a data recommendation method is provided, where managers can maintain and manage industry libraries, product libraries, and engineering node libraries. Managers can also add, edit, and modify the knowledge base / tool library. Engineers submit engineering logs every day (including work nodes, work content, operating equipment, etc.). When engineers browse the knowledge base / tool library (open a project, or send project information / current personnel information), the background will automatically calculate the recommended content and recommend personalized content to engineers, thereby improving the efficiency of engineers in searching for information. In addition, managers can continuously update the knowledge base / tool library based on the logs submitted by engineers, as well as updated knowledge and tools, to ensure the timeliness of the information searched by engineers and help engineers obtain the latest solutions in a timely manner.
[0117] This embodiment of the application can use advanced data analysis and machine learning technologies to monitor engineers' work processes and current industry trends in real time. By analyzing engineers' work patterns and needs, the system can intelligently push relevant tools, materials, and the latest information to support engineers' decision-making in project management, technology selection, and solution design.
[0118] The embodiment of the present application can more effectively integrate and associate multi-dimensional information resources through the comprehensive management of industry libraries, project node libraries, product libraries, knowledge bases and tool libraries; achieve comprehensive association in multiple dimensions, and improve the global visibility and utilization of information.
[0119] This embodiment of the application can intelligently filter and push information and tools that are highly relevant to the current engineering task based on real-time updated work logs and project information. This personalized and timely push method greatly improves engineers' work efficiency and decision-making accuracy.
[0120] This embodiment of the application uses an efficient tag association mechanism to ensure that every document, question and answer, or tool can be accurately categorized and retrieved. Compared with traditional manual categorization or simple keyword searches, this mechanism significantly reduces the time cost of information acquisition and improves data utilization and search results.
[0121] In an embodiment of the present application, a customized recommendation algorithm is designed for the specific work scenarios of automatic control engineers. It combines the work logs, project information, and tool requirements of automatic control engineers, and can more accurately understand and predict their information needs.
[0122] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.
[0123] Based on the same inventive concept, the present application also provides a data recommendation device for implementing the aforementioned data recommendation method. The solution provided by this device is similar to the solution described in the aforementioned method. Therefore, the specific limitations of one or more data recommendation device embodiments provided below can be found in the above-mentioned limitations of the data recommendation method and will not be repeated here.
[0124] Exemplarily, a data recommendation device is provided, which includes: a receiving module for responding to a trigger operation for a target project; an acquisition module for acquiring a contract number associated with the target project according to the trigger operation, and reading a work log corresponding to the target project based on the contract number; a parsing module for parsing the work log corresponding to the target project to obtain a tag set for the target project; a matching module for matching the tag set of the target project with knowledge tags in a target knowledge base, and searching for materials and tools associated with the target project; a screening module for screening target materials and target tools from the materials and tools associated with the target project based on a preset recommendation priority; and a display module for displaying the target materials and the target tools.
[0125] Exemplarily, the parsing module is specifically used to perform word segmentation extraction on the work log corresponding to the target project through a word segmenter to obtain several word segmentation results; verify the word segmentation results to obtain several labels of the target projects, and all the labels of the target projects constitute the label set of the target project.
[0126] Exemplarily, the screening module is specifically used to screen out candidate materials and candidate tools from the materials and tools associated with the target project according to the number of views and / or update time; sort the candidate materials and the candidate tools in descending order according to the number of views and / or update time; and use the top N candidate materials and the candidate tools as target materials and target tools; wherein N is a natural number greater than 0.
[0127] Exemplarily, the above device may further include:
[0128] A target knowledge base construction module is used to construct a target knowledge base based on the data files, question-and-answer knowledge, application tools, and instruction manuals of application tools that are needed by automatic control engineers during their work; establish a database table corresponding to the target knowledge base; the information in the database table includes: field name, type, and remarks;
[0129] The tag library construction module is used to establish a tag library based on industry, product, and project nodes; establish a tag library table corresponding to the tag library; the information in the tag library table includes: field name, type, and remarks.
[0130] Exemplarily, the above device may further include:
[0131] A knowledge updating module, configured to store updated knowledge into the target knowledge base, and / or
[0132] The work log submitted by the automatic control engineer is parsed, and a storage table is generated based on the parsing result, and the storage table is stored in the target knowledge base; the information in the storage table includes: field name, type, and remarks.
[0133] Exemplarily, the knowledge updating module is specifically used to extract the updated knowledge through a word segmenter to obtain a word segmentation set; perform intersection matching on the word segmentation set and the tag library to obtain an intersection result; after verifying the intersection result, obtain a tag set corresponding to the updated knowledge; and store the tag set corresponding to the updated knowledge in the target knowledge library.
[0134] Each module in the above-mentioned data recommendation device can be implemented in whole or in part through software, hardware, or a combination thereof. Each module can be embedded in or independent of the processor of the computer device in hardware form, or can be stored in the memory of the computer device in software form, so that the processor can call and execute the corresponding operations of each module.
[0135] In an exemplary embodiment, a computer device is provided, which may be a server. The computer device includes a processor, a memory, an input / output interface (I / O) and a communication interface. The processor, the memory and the input / output interface are connected via a system bus, and the communication interface is connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a data recommendation method is implemented.
[0136] In an exemplary embodiment, a computer device is provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.
[0137] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.
[0138] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.
[0139] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.
[0140] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile memory and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processor involved in the various embodiments provided herein may be, but are not limited to, a general-purpose processor, a central processing unit (CPU), a graphics processing unit (GPU), a digital signal processor (DSP), a programmable logic unit (PLC), a data processing logic unit based on quantum computing, an artificial intelligence (AI) processor, and the like.
[0141] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.
[0142] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.
Claims
1. A data recommendation method, characterized in that: The method comprises: responding to a trigger action on a target item; According to the trigger operation, obtaining the contract number associated with the target project, and reading the work log corresponding to the target project based on the contract number; Parse the work log corresponding to the target project to obtain a tag set for the target project; Matching the tag set of the target project with the knowledge tags in the target knowledge base to search for materials and tools associated with the target project; Based on a preset recommendation priority, select target materials and target tools from the materials and tools associated with the target project; The target information and the target tool are displayed.
2. The method according to claim 1, characterized in that The work log corresponding to the target project is parsed to obtain a tag set of the target project, including: Perform word segmentation extraction on the work log corresponding to the target project through a word segmenter to obtain several word segmentation results; The word segmentation result is verified to obtain labels of several target items, and the labels of all the target items constitute a label set of the target items.
3. The method according to claim 1, characterized in that The step of selecting target materials and target tools from the materials and tools associated with the target project based on the preset recommendation priority includes: Filter candidate materials and candidate tools from the materials and tools associated with the target project according to the number of views and / or update time; Arrange the candidate materials and the candidate tools in descending order according to the number of views and / or update time; The candidate materials and the candidate tools ranked in the top N are used as target materials and target tools; wherein N is a natural number greater than 0.
4. The method according to any one of claims 1 to 3, characterized in that Before responding to the trigger operation on the target item, the method further includes: Build a target knowledge base based on the data files, question-and-answer knowledge, application tools, and application tool manuals that automatic control engineers need to use during their work; Establishing a database table corresponding to the target knowledge base; the information in the database table includes: field name, type, and remarks; Establish a tag library based on industry, product, and project nodes; A tag library table corresponding to the tag library is established; the information in the tag library table includes: field name, type, and remarks.
5. The method according to claim 4, characterized in that The method further comprises: storing the updated knowledge in the target knowledge base, and / or, The work log submitted by the automatic control engineer is parsed, and a storage table is generated based on the parsing result, and the storage table is stored in the target knowledge base; the information in the storage table includes: field name, type, and remarks.
6. The method according to claim 5, characterized in that The storing of the updated knowledge into the target knowledge base includes: Extract the updated knowledge through the word segmenter to obtain a word segmentation set; Perform intersection matching on the word segmentation set and the tag library to obtain an intersection result; After verifying the intersection result, a label set corresponding to the updated knowledge is obtained; The tag set corresponding to the updated knowledge is stored in the target knowledge base.
7. A data recommendation device, characterized in that: The device comprises: A receiving module, configured to respond to a trigger operation on a target item; an acquisition module, configured to acquire the contract number associated with the target project according to the trigger operation, and read the work log corresponding to the target project based on the contract number; A parsing module, configured to parse the work log corresponding to the target project to obtain a tag set of the target project; A matching module, configured to match the tag set of the target project with the knowledge tags in the target knowledge base, and search for materials and tools associated with the target project; A screening module, configured to screen target materials and target tools from the materials and tools associated with the target project based on a preset recommendation priority; The display module is used to display the target data and the target tool.
8. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.
10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.