Proposal and Verification of Bidirectional Recommendation System for Learning Web Digital Texts

Recently, e-learning systems have begun to be used in companies and education institutions. The spread of e-learning is mainly due to development of the learning management system (LMS), which includes SCORM and WebCT. Therefore, the introduction of learning the web digital web digital texts have become much simpler. The increase of contents of the web digital texts has realized a wider range of learning. As a result, we are concerned that learners will be confused with selecting the best learning web digital texts. In our research, we are developing a bidirectional recommendation system that extracts the relationship among learning the web digital texts with historical logs and recommends an effective web digital text for learners. In this paper, we first discuss the design of the bidirectional recommendation system, and second, we show its evaluation results. Finally, we conclude that Our recommendation system is useful for learners.