The Research And Implementation Of Personalized Recommendation Learning Based On Knowledge In Teaching Platform

There were some shortcomings for providing recommended services for learners at this stage of the network teaching platform, with regard to the researches of personalized knowledge recommendation are few, this paper made a attempt in the research and implementation of personalized recommendation learning based on knowledge, by means of logical relationship of subject knowledge and the interest degree of knowledge points.This paper analyzed the theoretical foundation and guiding significance of the network teaching platform, and proposed knowledge point learning system based on these theoretical foundation and guiding significance; analyzed learner's cognitive level features, initialized students model which conformed to learner's individual level; then acquired the interest characteristics in knowledge and built a student model, took advantage of the hybrid algorithm which combined by content-based filtering recommendation algorithm and collaborative filtering recommendation algorithm, added a personalized recommendation module into the traditional learning website,helped learners to have the learning knowledge and non-learning knowledge associated, and thought this associate carefully to complete the construction of meaning.Knowledge-based personalized recommendation model in teaching platform provided learners with the knowledge learning consistent with their personality, guided learners to construct knowledge efficiently. It could not only satisfy the requirements of the large-scale study in modern society, but also provide learners with personalized learning services.This paper was a attempt which improved content-based filtering and collaborative filtering technology of e-commerce, and applied the specific subject knowledge structure to the network teaching platform.