상세정보
학술대회
Movie Recommendation using Metadata based Word2Vec Algorithm
- 발행일
- 201801
- 출처
- International Conference on Platform Technology and Service (PlatCon) 2018, pp.33-37
- 협약과제
- 18HS3100, 디지털콘텐츠 In-House R&D, 박수명
- 초록
- Nowadays, recommending preferable item among huge number of item is essential on online market. Many content platforms, such as YouTube and Amazon, use recommendation techniques to recommend items. Therefore, various techniques have been studied to recommend desirable item for each users. In this paper, we propose a method for effectively recommending preferable movies for each users by using community user's movie rating information and movie metadata information with deep learning technology. The proposed method shows 0.165 performance improvement based on Rcall@100 as compared with the basline method.
- KSP 제안 키워드
- Metadata information, Movie Recommendation, Movie rating, deep learning(DL), learning technology, performance improvement