Design And Implementation Of Teaching Discussion Platform And Its Key Technologies

With the continuous development of the Internet era,the teaching methods of courses have been changing.It has gradually shifted from the traditional teaching of teachers and students in all offline classrooms to online network platform-assisted teaching.More and more online teaching courses have emerged as the times require.In order to strengthen the interaction between teachers and students on the network platform and the students' online learning experience,the teaching discussion platform increases the discussion area.But after investigation and use,it is found that the design rationality and service quality of the discussion area need to be improved.This paper redesigns a reasonable mobile teaching discussion platform for the business of the teaching discussion area,as well as the key technology research for the improvement of the service quality of the platform.The paper designs and implements an emerging teaching discussion platform.In addition to the use of students and teachers,the platform adds a set of management mode and management authority of relevant roles.In the aspect of improving service quality,it mainly studies the recommendation of similar posts and the rational ranking of comment area,which improves user experience and learning efficiency.In the key technology aspect,this paper focuses on the similarity recommendation of posts for professional courses.Statistical machine learning method is used to study the similarity recommendation.After completing the keyword extraction and posts categorization in professional fields,through the analysis and construction of features and the combination of models,a model training recommendation method based on feature reconstruction and fusion is finally developed.Experiments show that this method has a good recommendation effect for business oriented to professional course discussion area.The paper also focuses on the ranking of content in the comment area.In this paper,an unsupervised computing method is used.With analyzing the characteristics of the discussion area,an iterative ranking method based on semantic similarity matrix is studied.This method is based on Page Rank's ranking idea,constructs similarity matrix,calculates the weight of each comment by iteration formula,and finally uses the weight to rank the comment.Experiments show that this method can accurately screen out high-quality comments and has a high recall rate in the recognition of invalid comments.Next,from the system aspect,through the analysis and investigation of the existing online education platform,the paper improves the system design and some functions of the original discussion area,separately extracts the comment area to form a new teaching discussion platform,and proposes a new management model,which adds two roles of teaching administrator and system administrator,and standardizes the use rights of all roles.Finally,according to the workflow of demand analysis,system overall design and detailed design,the paper carries out the system implementation of teaching discussion platform,and finally shows the system demonstration of mobile terminal.