Loose coupling type knowledge management system and construction method thereof

Abstract

The invention belongs to the technical field of enterprise knowledge management, and particularly relates to a loose coupling type knowledge management system comprising a resource layer used for collecting knowledge on departments and personal computers, including structured and unstructured data, converting the unstructured data into structured data for preliminary storage, and storing the structured data in a database; and meanwhile, an interface is designed for recording and synchronizing data. According to the system, efficient integration and sharing of knowledge are achieved, the quality and efficiency of enterprise knowledge management are remarkably improved, all kinds of knowledge are collected through the resource layer and converted into structured data to be stored, unified classification processing is conducted through the resource integration layer, dominant and implicit knowledge is stored through the resource library layer in a classified mode, employees can conveniently obtain the needed knowledge, and the enterprise knowledge management efficiency is improved. The knowledge searching time is shortened, the service layer provides multiple knowledge service functions, repeated labor and loss of knowledge are avoided, rich intangible knowledge assets are accumulated for enterprises, and the core competitiveness of the enterprises is enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of enterprise knowledge management, and in particular to a loosely coupled knowledge management system and a construction method thereof. Background Art

[0002] In the current context of the wave of economic globalization and the booming development of the knowledge economy, the enterprise competition pattern has undergone profound changes, and knowledge resources have become the core elements for enterprises to compete in the market. Along with the rapid changes in the market environment, enterprises are facing numerous challenges, and the key role of knowledge management in ensuring the stable development of enterprises and enhancing their core competitiveness has become increasingly prominent. It is not only the internal driving force for enterprise innovation and development but also an inevitable choice for enterprises to achieve sustainable development in the era of knowledge economy. How to efficiently explore, innovate, and apply knowledge has become a key issue for enterprises to seek development.

[0003] There are generally shortcomings in the knowledge management field of Chinese construction enterprises. They overly rely on external knowledge, and the internal knowledge management mechanism urgently needs to be improved. The massive knowledge resources generated during the project construction process have not been properly managed and fully utilized. The knowledge precipitation and update are lagging behind, resulting in serious waste of resources, which is extremely unfavorable to the long-term development of enterprises. The knowledge characteristics of construction enterprises exacerbate the management difficulty. Their knowledge has obvious incoherence, with large differences in knowledge at each stage of the project; the complexity is prominent, involving multi-disciplinary knowledge; although there are repetitions between projects, unique technical and management knowledge cannot be shared among enterprises. These problems have made it extremely difficult for construction enterprises in the practice of knowledge management.

[0004] Chinese construction enterprises have a complete industrial chain integrating "planning, design, investment, construction, and operation", and actively expand their businesses in multiple fields such as energy and power, municipal culture and tourism, and ecological environment protection. During long-term production and operation activities, they have accumulated massive knowledge with great reuse and reference value, covering multiple aspects such as design and research results, market research and planning, investment experience, performance implementation ideas and methods, and enterprise management experience. However, this knowledge is currently scattered in employees' brains, personal computers, and various databases, lacking effective integration and management. Due to the lack of a knowledge management platform, these scattered knowledge cannot be transformed into organizational knowledge and are difficult to play a guiding role in employees' daily work and innovation.

[0005] In the context of the knowledge economy and the information age, traditional industries are facing the urgent task of transformation and upgrading, and the importance of knowledge management has become even more prominent. For Chinese construction enterprises, if they cannot introduce and improve the knowledge management system in a timely manner, the development of enterprises will inevitably be hindered. Therefore, it is extremely urgent to carry out the research and development of a loosely coupled multi-level knowledge management system, which is the key for enterprises to break through the development bottleneck and achieve sustainable development. Summary of the Invention

[0006] (1) Technical problems to be solved

[0007] In view of the deficiencies of the prior art, the present invention provides a loosely coupled knowledge management system and a construction method thereof, which solve the problems raised in the above-mentioned background art.

[0008] (2) Technical solutions

[0009] In order to achieve the above object, the present invention specifically adopts the following technical solutions:

[0010] A loosely coupled knowledge management system, comprising:

[0011] Resource layer: used to collect knowledge on departmental and personal computers, including structured and unstructured data, convert unstructured data into structured data for preliminary storage, and design interfaces for collecting and synchronizing data;

[0012] Resource integration layer: integrates and processes the data of the resource layer, classifies them uniformly, and provides a standardized data format for the upper layer;

[0013] Resource library layer: stores the explicit knowledge within the enterprise and the mined implicit knowledge according to the knowledge base classification directory to form a structured knowledge base;

[0014] Service layer: provides knowledge service functions including knowledge management, unified retrieval, expert consultation, knowledge community, learning and training platform;

[0015] Application layer: based on the functions of the service layer, combined with business scenarios, realizes the automation and scenarioization of knowledge management, constructs a job knowledge map and a business process knowledge map, and helps talent cultivation and business empowerment;

[0016] Display layer: displays knowledge in a visual way, facilitates users to obtain and use knowledge, and supports employees to independently create and flexibly modify process knowledge maps.

[0017] Furthermore, the system further includes a master data management system, which is used to manage the data specifications and associations of each business system, management system and external system, ensure the standardization and uniqueness of the enterprise's master data, and ensure the effectiveness of the relevant system data and the integration of interactions.

[0018] Furthermore, the unified retrieval function realizes advanced and efficient retrieval of multiple databases with one key through unified heterogeneous, keyword retrieval and full-text retrieval.

[0019] Furthermore, the system uses knowledge graphs, machine learning, and big data technologies to integrate business big data and embed it in the entire innovation process to provide a basis for scientific decision-making, including intelligent prediction of project risk points, providing risk point avoidance measures, and providing an intelligent financial calculation of the best investment portfolio.

[0020] A construction method for a loosely coupled knowledge management system, comprising the following steps:

[0021] Requirement analysis stage: Analyze the current situation and limitations of enterprise knowledge management, and analyze the feasibility and applicability of building a company's knowledge management system from two aspects: the knowledge base architecture, knowledge base classification, knowledge management application function requirements, and system performance and security non-functional requirements, and formulate corresponding countermeasures;

[0022] System design stage: Establish a knowledge management, operation system, management, assessment, and incentive system. Based on the results of requirement analysis, design the framework structure, function architecture, knowledge base, processing flow, security, and performance of the knowledge management system, determine that the system consists of a resource layer, a resource integration layer, a resource library layer, a service layer, an application layer, and a presentation layer from bottom to top, and refine the function design of each layer to form a design specification for a loosely coupled knowledge management system and a project implementation plan;

[0023] System development and practice stage: According to the design specification and implementation plan, conduct system research and development, including five stages: system development, installation and debugging, testing, trial operation, and acceptance. Develop a user operation manual and a system training manual, organize personnel to test and trial operate the system functions, and optimize the system according to the problems and requirements feedback during the practice process, and finally realize the system go-live.

[0024] Further, in the requirement analysis stage, through the methods of knowledge classification interviews and key knowledge area research with enterprise employees, conduct research on knowledge classification standards to provide a basis for building a knowledge classification system.

[0025] Further, in the system design stage, when constructing a knowledge system, first formulate a classification standard that conforms to the company's knowledge, conduct preliminary design, global adjustment, pilot verification, and optimization and improvement, clarify the knowledge classification management process and data transmission and application processes, construct a knowledge map and a knowledge graph, deploy the knowledge classification system, and establish an enterprise knowledge base and a multi-dimensional knowledge display and sharing platform.

[0026] Further, in the system development and practice stage, the testing process includes test preparation and detailed testing, form a system test plan, and conduct a comprehensive test on the functions, performance, and security of the system.

[0027] Further, in the system trial operation stage, improve and optimize the system, solve the problems found during the trial operation process, and improve the stability and reliability of the system.

[0028] Further, in the project training stage, after completing system testing and optimizing the system, conduct training for users, form a user operation manual and a system training manual to ensure that users can use the system proficiently.

[0029] (3) Beneficial effects

[0030] Compared with the prior art, the present invention provides a loosely coupled knowledge management system and its construction method, having the following beneficial effects:

[0031] This system realizes the efficient integration and sharing of knowledge, significantly improves the quality and efficiency of enterprise knowledge management. By collecting various types of knowledge in the resource layer and converting it into structured data for storage, the resource integration layer conducts unified classification and processing, and the resource library layer stores explicit and implicit knowledge in categories. Employees can conveniently obtain the required knowledge, reducing the time for knowledge searching. The service layer provides various knowledge service functions, such as unified retrieval that can retrieve multiple databases with one key, and the knowledge community promotes employee communication and interaction, facilitating knowledge flow and innovation. This not only avoids duplicate labor and loss of knowledge but also accumulates rich intangible knowledge assets for the enterprise, enhancing the core competitiveness of the enterprise.

[0032] This system is closely combined with business scenarios, strongly promoting talent cultivation and business empowerment. The application layer constructs job knowledge maps and business process knowledge maps, closely associating knowledge with specific businesses. New employees can quickly familiarize themselves with the work content and processes with the help of job knowledge maps, shortening the growth cycle; business process knowledge maps assist employees in obtaining relevant knowledge in a timely manner during project execution, improving work efficiency and quality. In addition, the system uses knowledge graphs and big data technologies to provide a basis for scientific decision-making, intelligently predicting project risk points and giving avoidance measures, realizing the automation and scenario-based management of knowledge, and comprehensively promoting the development of enterprise business. Brief Description of the Drawings

[0033] Figure 1 is the architecture diagram of the loosely coupled knowledge management system of the present invention;

[0034] Figure 2 is the flow chart of the construction method of the loosely coupled knowledge management system of the present invention;

[0035] Figure 3 is the interaction diagram of the functional modules of the loosely coupled knowledge management system of the present invention. Detailed Embodiments

[0036] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0037] Embodiment

[0038] As Figures 1-3As shown in the figure, a loosely coupled knowledge management system proposed by an embodiment of the present invention includes:

[0039] Resource layer: Use specially developed data collection tools to collect knowledge data from the computers of each department in the company and the personal computers of employees. Adopt advanced natural language processing technology and data parsing algorithms to convert unstructured data, such as documents, emails, reports, etc., into structured data. Taking the construction plan document of a certain project as an example, extract key information, such as project background, construction process, technical key points, etc., through technical means, and store it in a distributed file system. At the same time, design a standardized interface to ensure the timely collection and synchronization of data;

[0040] Resource integration layer: Use ETL tools and data cleaning algorithms to integrate the data in the resource layer. For data from different sources and formats, formulate unified data standards and specifications, remove duplicate data, and correct incorrect data. When integrating design drawings and construction record data, unify the coordinate system, measurement unit, etc. in the data to provide standardized and high-quality data for the upper layer;

[0041] Resource library layer: Store explicit knowledge and mined implicit knowledge according to the pre-established knowledge base classification directory. Explicit knowledge is directly stored through a data import tool, while implicit knowledge is transformed into a storable knowledge form through knowledge extraction technology. In a certain new energy project, organize the experience and lessons of engineers during the project implementation process into documents and store them in the corresponding project experience knowledge base for subsequent project reference;

[0042] Service layer: Develop a knowledge management module to implement functions such as knowledge classification, review, and release; build a unified retrieval platform, integrate unified heterogeneous, keyword retrieval, and full-text retrieval technologies to meet the diverse retrieval needs of users; establish an expert consultation module to provide professional guidance for employees through methods such as online expert Q&A and case sharing; build a knowledge community to promote knowledge exchange and interaction among employees; build a learning and training platform, upload various training courses and learning materials to support employees' self-study;

[0043] Application layer: Combine the company's business scenarios, such as project bidding, construction management, operation and maintenance, etc., to develop job knowledge maps and business process knowledge maps. In the project bidding scenario, bidders can quickly obtain knowledge such as the bidding process, required qualifications, and previous successful cases through the job knowledge map; the business process knowledge map associates each link in the project construction process with relevant knowledge to facilitate talent cultivation and efficient business development;

[0044] Presentation layer: By using visualization technologies such as data dashboards and chart displays, knowledge is presented to users in an intuitive and easy-to-understand manner. Employees can easily obtain the required knowledge through the operation interface and can also independently create and flexibly modify process knowledge maps to meet personalized needs.

[0045] The system also includes a master data management system for managing data specifications and associations among various business systems, management systems, and external systems, ensuring the standardization and uniqueness of enterprise master data, and guaranteeing the effectiveness of relevant system data and the integration of interactions.

[0046] The unified retrieval function realizes advanced and efficient retrieval of multiple databases with one key through unified heterogeneous, keyword retrieval, and full-text retrieval.

[0047] The system uses knowledge graphs, machine learning, and big data technologies to integrate business big data and embed it in the entire innovation process to provide a basis for scientific decision-making, including intelligent prediction of project risk points, provision of risk point avoidance measures, and provision of intelligent financial calculation optimal investment portfolios; existing technologies often face problems such as scattered storage of knowledge resources, inconsistent classification standards, and serious system data islands. However, this system collects and integrates various types of knowledge through the resource layer to achieve structured storage; the resource integration layer unifies data standards to ensure data quality. The service layer has rich and diverse functions, and the application layer develops knowledge maps closely combined with business scenarios. In particular, the use of knowledge graphs and big data technologies to provide support for scientific decision-making, which many existing systems do not have, can more efficiently achieve knowledge management and business empowerment.

[0048] Such as Figures 2-3 As shown, a construction method for a loosely coupled knowledge management system includes the following steps:

[0049] Requirement analysis stage: Analyze the current situation and limitations of enterprise knowledge management, and analyze the feasibility and applicability of building a company's knowledge management system from two directions: the knowledge base architecture, knowledge base classification, knowledge management application function requirements, and system performance and security non-functional requirements, and formulate corresponding countermeasures;

[0050] Establish a research group consisting of business experts, technical personnel, and management personnel. Through questionnaires, interviews, seminars, etc., comprehensively analyze the current situation and limitations of the company's knowledge management. Distribute 300 questionnaires to employees in different positions, covering multiple positions such as design, construction, and management, and deeply understand their requirements for the knowledge base architecture, classification, and knowledge management applications. At the same time, evaluate from aspects such as system performance and security, analyze the feasibility and applicability of system construction, and formulate detailed countermeasures;

[0051] System Design Phase: Establish a knowledge management, operation system, and management, assessment, and incentive system. Based on the results of the requirements analysis, design the framework structure, functional architecture, knowledge base, processing flow, security, and performance of the knowledge management system. Determine that the system consists of a resource layer, a resource integration layer, a resource library layer, a service layer, an application layer, and a presentation layer from bottom to top, and refine the functional design of each layer to form a loosely coupled knowledge management system design specification and project implementation plan;

[0052] Establish a sound knowledge management, operation system, and management, assessment, and incentive system. Clarify the responsibilities of each department in knowledge management, formulate assessment indicators for knowledge contribution, and link employees' knowledge contribution with performance. Based on the results of the requirements analysis, conduct a detailed design of the system's framework structure, functional architecture, knowledge base, processing flow, security, and performance. Invite industry experts to review the design plan and optimize it according to the review opinions to form the final design specification and project implementation plan;

[0053] System Development and Practice Phase: According to the design specification and implementation plan, conduct system research and development, including five stages: system development, installation and commissioning, testing, trial operation, and acceptance. Develop a user operation manual and system training materials, organize personnel to test and conduct trial operation on the system functions, and optimize the system according to the problems and requirements feedback during the practice process, and finally achieve the system go-live;

[0054] According to the design plan, organize a professional development team to conduct system development. During the development process, strictly follow the agile development method and conduct regular code reviews and tests. After development, conduct installation and commissioning, and simulate various actual business scenarios for testing, including scenarios such as high-concurrency access and large-data volume storage. Invite some employees to conduct trial operation, collect feedback problems, such as the operation interface is not friendly enough, the retrieval speed is slow, etc., and optimize them in a timely manner;

[0055] After the system testing and optimization are completed, formulate a detailed training plan. Design personalized training courses for employees in different positions, including system function introduction, operation demonstration, actual case drills, etc. Adopt a training method that combines online and offline. Provide learning materials online through video tutorials, online documents, etc., and organize centralized training and on-site guidance offline. After the training, assess the employees to ensure that they can use the system proficiently. At the same time, form a detailed user operation manual and system training materials for employees to consult at any time.

[0056] In the requirements analysis stage, conduct a research on the knowledge classification standard through methods such as knowledge classification interviews and key knowledge area research on enterprise employees to provide a basis for constructing a knowledge classification system.

[0057] In the system design stage, when constructing the knowledge system, first formulate a classification standard that conforms to the company's knowledge, conduct preliminary design, global adjustment, pilot verification, optimization and improvement, clarify the knowledge classification management process and data transmission and application processes, construct a knowledge map and a knowledge graph, deploy the knowledge classification system, and establish an enterprise knowledge base and a multi-dimensional knowledge display and sharing platform.

[0058] In the system development and practice stage, the testing process includes test preparation and detailed testing, forming a system test plan, and comprehensively testing the functions, performance, and security of the system.

[0059] In the system trial operation stage, improve and optimize the system, solve the problems found during the trial operation process, and improve the stability and reliability of the system.

[0060] In the project training stage, after completing the system testing and optimizing the system, train the users, form a user operation manual and a system training textbook to ensure that the users can use the system proficiently;

[0061] Existing methods may lack comprehensive and in-depth requirements analysis and insufficient attention to the needs of employees in different positions. In the requirements analysis stage of this method, a professional research team is formed to widely collect the needs of employees in different positions through various methods and comprehensively evaluate the feasibility of the system. In system design, the construction of the knowledge system is more rigorous and undergoes optimization through multiple links. In system development and practice, agile development is adopted, focusing on multi-scenario testing and user feedback optimization. The project training stage is also more targeted, designing personalized courses for different positions. These are the significant differences from the existing technologies and can better ensure the practicality and effectiveness of the system.

[0062] Finally, it should be noted that the above are only the preferred embodiments of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, for those skilled in the art, they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A loosely coupled knowledge management system, characterized in that, Including: Resource layer: Used to collect knowledge on the department and personal computers, including structured and unstructured data, convert unstructured data into structured data for preliminary storage, and design interfaces for collecting and synchronizing data; Resource integration layer: Integrates and processes the data in the resource layer, classifies them uniformly, and provides a standardized data format for the upper layer; Resource library layer: Stores the explicit knowledge within the enterprise and the mined implicit knowledge according to the knowledge library classification directory, forming a structured knowledge library; Service layer: Provides knowledge service functions including knowledge management, unified retrieval, expert consultation, knowledge community, learning and training platform; Application layer: Based on the functions of the service layer, combined with business scenarios, realizes the automation and scenario-based knowledge management, constructs the post knowledge map and business process knowledge map, and helps with talent cultivation and business empowerment; Presentation layer: Displays knowledge in a visual way, facilitates users to obtain and use knowledge, and supports employees to independently create and flexibly modify the process knowledge map.

2. The loose coupling type knowledge management system according to claim 1, characterized in that The system also includes a master data management system, which is used to manage the data specifications and associations of each business system, management system and external system, ensure the standardization and uniqueness of the enterprise's master data, and guarantee the effectiveness of the relevant system data and the integration of interactions.

3. A loose-coupling knowledge management system according to claim 1, wherein The unified retrieval function realizes the advanced and efficient retrieval of multiple databases with one key through unified heterogeneous, keyword retrieval and full-text retrieval.

4. A loose-coupling knowledge management system according to claim 1, characterized in that, The system utilizes knowledge graph, machine learning, and big data technologies, integrates business big data, and embeds it into the entire innovation process to provide a basis for scientific decision-making, including intelligent prediction of project risk points, providing risk point avoidance measures, and providing intelligent financial calculation of the best investment portfolio.

5. A construction method of a loosely coupled knowledge management system, characterized in that Including the following steps: Requirement Analysis phase: Analyze the current situation and limitations of the enterprise's knowledge management, analyze the feasibility and applicability of the company's knowledge management system construction from two directions: the knowledge library architecture, knowledge library classification, knowledge management application function requirements, and system performance and security non-functional requirements, and formulate corresponding countermeasures; System design phase: Establish a knowledge management, operation system, management, assessment, and incentive system. Based on the results of the requirement analysis, design the framework structure, function architecture, knowledge library, processing process, security, and performance of the knowledge management system, determine that the system consists of a resource layer, a resource integration layer, a resource library layer, a service layer, an application layer, and a presentation layer from bottom to top, and refine the function design of each layer to form a loosely coupled knowledge management system design specification and project implementation plan; System development and practice phase: According to the design specification and implementation plan, conduct system research and development, including five stages: system development, installation and commissioning, testing, trial operation, and acceptance, formulate user operation manuals and system training materials, organize personnel to test and trial run the system functions, and optimize the system according to the problems and requirements feedback during the practice process, and finally realize the system go live.

6. The construction method of a loosely coupled knowledge management system according to claim 5, characterized in that, In the requirement analysis phase, through the methods of knowledge classification interviews and key knowledge area investigations with enterprise employees, conduct research on knowledge classification standards to provide a basis for constructing a knowledge classification system.

7. The construction method of a loosely coupled knowledge management system according to claim 5, characterized in that In the system design phase, when constructing the knowledge system, first formulate a classification standard that conforms to the company's knowledge, conduct preliminary design, global adjustment, pilot verification, optimization and improvement, clarify the knowledge classification management process and data transmission and application processes, construct a knowledge map and a knowledge graph, deploy the knowledge classification system, and establish an enterprise knowledge base and a multi-dimensional knowledge display and sharing platform.

8. The construction method of a loosely coupled knowledge management system according to claim 5, characterized in that In the system development and practice phase, the testing process includes test preparation and detailed testing, form a system test plan, and conduct comprehensive testing on the functions, performance, and security of the system.

9. A method for constructing a loosely coupled knowledge management system according to claim 5, characterized in that, In the system trial operation phase, improve and optimize the system, solve the problems found during the trial operation process, and improve the stability and reliability of the system.

10. The construction method of a loosely coupled knowledge management system according to claim 5, characterized in that In the project training phase, after completing system testing and optimizing the system, train the users, form a user operation manual and a system training manual to ensure that the users can use the system proficiently.

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