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Conference Paper
Movie Recommendation using Metadata based Word2Vec Algorithm
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- Authors
- Yeo Chan Yoon, Jun Woo Lee
- Issue Date
- 2018-01
- Citation
- International Conference on Platform Technology and Service (PlatCon) 2018, pp.33-37
- Language
- English
- Type
- Conference Paper
- Project Code
- 18HS3100, Digital Content In-House R&D, Park Soo-Myung
- Abstract
- 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 Keywords
- Metadata information, Movie Recommendation, Movie rating, deep learning(DL), learning technology, performance improvement