Micro Course Recommendation Model Optimization based on User Behavior
Xiangbin Gao, Lian Wang
Available Online April 2017.
- https://doi.org/10.2991/iemss-17.2017.165How to use a DOI?
- Recommendation Model; Search Engine; Micro Course; User Interest.
- With the advent of the information era, it has brought a change to the education industry. As the network educational resources gradually increased, to obtain individual needs in the massive resources has become a headache problem for users. In the use of traditional search engines for information retrieval, users need to actively input the retrieval keywords, and the search results have no users individualization feature. In this case, recommendation technology has emerged as a complementary technique for search engine. In this paper, we combined recommendation technology with micro course system in the education field, through the establishment of user interest model, at last made use of the recommendation algorithm based on users as the bridge to link the user interest and micro course video resources, presented the video resources that users are satisfied with and interested in to the user, and completed personalized video recommendation. The combination of the recommendation model and the micro course has a positive effect on reducing the time needed to retrieve the video resources and improving the learning and working efficiency of teachers and students.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Xiangbin Gao AU - Lian Wang PY - 2017/04 DA - 2017/04 TI - Micro Course Recommendation Model Optimization based on User Behavior BT - Proceedings of the 2017 International Conference on Innovations in Economic Management and Social Science (IEMSS 2017) PB - Atlantis Press SP - 843 EP - 849 SN - 2352-5428 UR - https://doi.org/10.2991/iemss-17.2017.165 DO - https://doi.org/10.2991/iemss-17.2017.165 ID - Gao2017/04 ER -