Research On The Construction And Application Of MOOC Unified Platform

With the rapid development of the Internet,the teaching model of "Internet +Education" has made great progress and development.As a typical representative,MOOC has been recognized and appreciated by well-known universities and educational institutions.Many well-known universities and educational institutions have conducted in-depth research and exploration in this field.The school network launched by Tsinghua University in China,the Chinese language class launched by Peking University,and the good university online launched by Shanghai Jiaotong University.Edx from MIT and Harvard University,and Coursera founded by Stanford University.With the increasing number of MOOC platforms and the rapid increase of course resources under the same MOOC platform,the curriculum resources on the MOOC platform are heterogeneous,complicated and redundant,which causes users to fall into the predicament of information overload and knowledge voyage.Therefore,how to uniformly manage the curriculum resources on many MOOC platforms and realize fast cross-platform retrieval,and how to provide effective course recommendation services for users has become an urgent problem to be solved in the current MOOC platform.This paper first uses Jsoup to crawl the course resources and related information on each well-known MOOC platform,and pre-processes the obtained source data,such as filling in missing values,translating,and gender recognition of teacher avatars.After processing,it is stored in MySQL database.According to the mapping rules between ontology and relational database,the table data of relational database is automatically mapped into MOOC domain ontology,thus completing the automatic construction of MOOC domain ontology and realizing the semantic expression of MOOC platform curriculum resources.The constructed MOOC domain ontology is parsed into a triple form by Jena,and the obtained triplet file is uploaded to HDFS and loaded into the HBase database.The automatic construction of the MOOC domain ontology and the use of HBase storage can not only effectively solve the problems of heterogeneous,complicated and redundant curriculum resources in the MOOC platform,but also facilitate the extension of the ontology of the MOOC domain.Then,by analyzing the MOOC platform,the course characteristics of the MOOC platform are extracted,and a semantic retrieval model is constructed based on the characteristics of the course.Aiming at the shortcomings of the existing distributed course recommendation algorithm with low recommendation accuracy,an improved distributed course recommendation algorithm is designed.The improved distributedcourse recommendation algorithm is to add the course features to the existing distributed course recommendation algorithm.According to the characteristics of these courses,a similarity calculation model is constructed to calculate the similarity of the courses obtained by the original algorithm,according to the similarity level.A list of recommended course resources.This model is used in the course retrieval to calculate the semantic similarity of the course objects,and is pushed to the user according to the similarity from high to low.The experimental results show that the constructed semantic retrieval model can improve the accuracy of course retrieval to a certain extent.After comparative analysis,the improved distributed course recommendation algorithm can effectively improve the accuracy of course recommendation to a certain extent.Finally,a unified and unified MOOC platform was designed and developed.Based on the above theory and related technologies,a unified MOOC platform was developed using the J2 EE architecture,and semantic retrieval and course recommendation services were implemented under the platform.