文章基本信息

标题：Improving Web Movie Recommender System Based on Emotions
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作者：Karzan Wakil ; Rebwar Bakhtyar ; Karwan Ali 等
期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2015
卷号：6
期号：2
DOI：10.14569/IJACSA.2015.060232
出版社：Science and Information Society (SAI)
摘要：Recommender Systems (RSs) are garnering a significant importance with the advent of e-commerce and e-business on the web. This paper focused on the Movie Recommender System (MRS) based on human emotions. The problem is the MRS need to capture exactly the customer’s profile and features of movies, therefore movie is a complex domain and emotions is a human interaction domain, so difficult to combining together in the new Recommender System (RS). In this paper, we prepare a new hybrid approach for improving MRS, it consists of Content Based Filtering (CBF), Collaborative Filtering (CF), emotions detection algorithm and our algorithm, that presented by matrix. The result of our system provides much better recommendations to users because it enables the users to understand the relation between their emotional states and the recommended movies.
关键词：thesai; IJACSA; thesai.org; journal; IJACSA papers; movie recommender system; collaborative filtering; content based filtering; emotion; CF; CBF; MRS