Research On Personalized Recommendation Of MOOC Resources

The unique features of MOOC lead to the diversity of learners in terms of media preference,background knowledge,language preference and so on.It is difficult for learners to find suitable and interesting courses in a large amount of curriculum resources.How in the multitude of curriculum resources of high quality,fast and accurate screening to satisfy the individualized learning characteristics of the curriculum object has become an urgent problem to be solved.To construct the curriculum resources through semantic Web,can realize the semantic knowledge representation,accurately describe the relationship between the knowledge.The application of semantic Web to MOOC platform can effectively improve the effectiveness of MOOC platform curriculum recommendation.First,according to the “Classification China Library” to construct a curriculum resource ontology based on the division of each field and the structural characteristics of the course in MOOC platform.Before the recommendation of the course,we need to obtain the learner's personality characteristics.By referring to the PAPI learner model,this paper constructs a learner ontology,which is used to collect the learner's personalized information,as to provide students with personalized recommendation of the course of another main objectThen,according to the deficiency and shortcoming of the traditional semantic similarity model and combine the actual demand,to improve the traditional semantic similarity calculation model.By studying the relationship between comprehensive evaluation and integration of curriculum object similarity between individual characteristics and the properties of the object and the current curriculum are learning courses and other courses of the distance of the object object similarity,proposes a knowledge point intelligent search algorithm;By integrating the comprehensive evaluation of the curriculum object,the similarity of the learner's individual characteristics and the course object attributes,a personalized curriculum algorithm is to be recommended.The improved algorithm is compared with the traditional algorithm,and the results show that the improved two algorithms have higher superiority..Finally,this paper designs and develops a MOOC resource personalized recommendation system.The experimental results show that this study can not only help learners understand the relationship between courses,Can also make the curriculum object in accordance with the needs of the learner's personality,from high to low to the learners,to help learners quickly find the right course object.