Research On Internal Knowledge Service Methods For Digital Learning

Innovation plays an important leading role in economic and social development.Scientific and technological innovation is the strategic support to improve social productivity and comprehensive national strength,and is the core of national development.In promoting enterprise innovation,knowledge is the most basic factor of production.Knowledge innovation determines the ability and level of enterprise innovation and development.The improvement of enterprise knowledge innovation ability comes from accurate and efficient knowledge service acquisition.In the era of Internet plus and post epidemic,the process of digital learning has intensified.New technologies have expanded the connotation of digital learning and promoted the deep digitalization of all links in knowledge services.In this context,how to build a more scientific and efficient enterprise knowledge service system for e-learning is of great practical significance to continuously improve the internal innovation ability and create the core competitive advantage of enterprises.This paper focuses on the operation mechanism and model method of enterprise knowledge service system for e-learning.This paper constructs the enterprise internal knowledge service system for e-learning;proposes the construction method of enterprise knowledge service based on knowledge map;constructs the multidimensional knowledge recommendation method based on deep learning;and constructs the knowledge service evaluation system from the dual perspectives of enterprises and employees of knowledge service.Focusing on the enterprise knowledge service in the context of e-learning,the research is carried out from three aspects:knowledge service content construction method,knowledge service recommendation method and knowledge service evaluation method.This paper focuses on the operation mechanism and model method of enterprise knowledge service system for e-learning.This paper constructs the enterprise internal knowledge service system for e-learning;proposes the construction method of enterprise knowledge service based on knowledge map;constructs the multidimensional knowledge recommendation method based on deep learning;and constructs the knowledge service evaluation system from the dual perspectives of enterprises and employees of knowledge service.Focusing on the enterprise knowledge service in the context of e-learning,the research is carried out from three aspects:knowledge service content construction method,knowledge service recommendation method and knowledge service evaluation method.1.In the construction of knowledge service content,how to mine the knowledge service system from a large number of explicit and discrete information,so as to form a more complete knowledge service content is a key research problem.This paper constructs an enterprise knowledge service model oriented to core concerns,mines the structured knowledge points by using text information extraction technology and forms a systematic enterprise knowledge system based on logical relationships between knowledge points by using knowledge mapping technology.Taking telecommunications industry as an example,selecting 5G technology as the core,an telecommunication enterprise knowledge system can be established focuses on 5G technology..In this paper,white papers,patents,academic literature,books and so on are used as data sources,named entity recognition models such as LSTM+CRF?BERT+CRF are adopted to automatically extract entities of industry,technology,product and build four relationships between the above entities including hyponymy,inclusion,association and application.On this basis,Neo4 j database is used to establish a 5G knowledge map and provides a visualized,systematic and searchable knowledge services for enterprises.The experimental results show that this method can effectively mine the knowledge service content needed by enterprises,and has practical significance.2.In terms of accurate recommendation of knowledge services,how to provide more accurate enterprise knowledge services for the personalized needs of employees is also a practical problem.In this paper,based on the enterprise digital learning scene,taking the course recommendation as an example,the enterprise training course recommendation model is constructed.Based on the historical learning records of students,word2 vec is used to realize the semantic representation of course text,LSTM is used to mine students' preferences,and attention mechanism is added to realize the dynamic mining of students' interests,which makes the course recommendation more intelligent and personalized.Firstly,the fundamental course recommendation model is built based on LSTM,and the following research is carried out based on the characteristics of enterprise internal course learning and training: First,through the course attention mechanism,the analysis of the historical learning records of students plays a role in judging whether to accept the courses to be recommended.Second,design enterprise plan attention mechanism,we can pay attention to the technical keywords in the enterprise plan in the recommendation process,and analyze whether the enterprise plan plays a role in the course recommendation.Third,the introduction of job attention to reflect the differences of students' positions,and analyze whether different positions play a role in course recommendation.The effect of each model is verified by different comparative experiments of enterprise actual data sets.3.In the aspect of knowledge service evaluation system,there are many factors affecting the evaluation effect,including the knowledge service at the enterprise level and the learning situation at the student level.Which factors will have a more significant impact on the effect of knowledge service needs further research.This paper analyzes the influencing factors of knowledge service from two aspects.On the knowledge supply side,it mainly evaluates the quality of knowledge service.On the knowledge internalization side,it mainly evaluates the performance of e-learning.One is to design the theoretical model of enterprise knowledge service based on the theory of service quality;the other is to build the digital learning behavior model based on the theory of engagement learning.The evaluation index for knowledge service process and the performance index for e-learning are constructed respectively.Based on the survey data and online learning data of enterprises,this paper makes a quantitative evaluation by means of multiple regression measurement,discovers the key factors affecting the effect of knowledge service,and puts forward corresponding countermeasures and suggestions according to the results of data analysis,which has enlightenment significance for the development of enterprise knowledge services.The research provides theoretical research and practical guidance for e-learning oriented enterprise knowledge service.It helps to promote the construction of enterprise internal knowledge service system and the universal extension of action mechanism.It provides the guidance of scientific construction method through the construction of knowledge service content system.It realizes the improvement of thousands of people's accurate learning efficiency through the research of knowledge service recommendation matching and the scientific construction of knowledge service.The construction of evaluation methods can further improve the effectiveness of knowledge services.