Emotions based movie recommender systems감정 기반 영화 추천 시스템

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In this study we focus on development of emotions based movie recommender system. Emotions based movie recommender systems have the potential to provide personalized recommendations by matching movie affective content with user emotional needs and preferences. The user emotional preferences can be affected by such factors as mood, social context and personality, which are hard to infer in unobtrusive manner. We propose a new approach to infer user emotional preferences based on the affective content of the previously watched movies. We explore the potential of emotions mined from the review text to to resemble the actual emotions the movie induces from the viewers. Unsupervised emotion detection methods based on vector space model are used to extract emotions and build emotion profile for each movie which we further incorporate into state-of-the-art model for rating prediction and elicitation of user emotional preferences. We show promising results from application of emotions in movie recommender systems and propose possible way to analyze obtained movie and user emotional profiles with the aim to get more insights on the user preferences.
Advisors
Yi, Mun Yongresearcher이문용researcher
Description
한국과학기술원 :지식서비스공학대학원,
Publisher
한국과학기술원
Issue Date
2019
Identifier
325007
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 지식서비스공학대학원, 2019.8,[iv, 48 p. :]

Keywords

movie recommender system▼aemotions in movies▼amovie reviews▼aemotion detection in text▼apreference elicitation; 영화 추천 시스템▼a영화에서의 감정▼a영화 리뷰▼a텍스트에서의 감정 감지▼a선호도 도출

URI
http://hdl.handle.net/10203/283120
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=875543&flag=dissertation
Appears in Collection
KSE-Theses_Master(석사논문)
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