DocumentCode :
1791275
Title :
Layered recommendation: A new strategy for movie promotion
Author :
Dengxiang Liu ; Xianzhong Wang ; Hongtao Lu
Author_Institution :
Sch. of Electron. Inf. & Electr. Eng., Shanghai Jiaotong Univ., Shanghai, China
fYear :
2014
fDate :
14-16 Oct. 2014
Firstpage :
73
Lastpage :
77
Abstract :
Traditional Top-N strategy for movie recommendation takes only users´ ratings into account when mining users´ needs or interests. But watching movie is a special behavior, in which users´ interests should not just be represented by their ratings. We think that the decision to watch a movie also reflects the target users´ needs, even though he or she may give it a low rating. In this paper, we introduce two factors, i.e. Users´ Tastes and Users´ Choices to describe users´ needs. The analysis of relationships between them gives us a new explanation for the layered structure of users´ ratings. Then, inspired by Maslow´s Hierarchy of Needs theory, we present a layered perspective of users´ interests and design an efficient and effective recommendation strategy based on collaborative filtering models to meet users´ layered needs.
Keywords :
collaborative filtering; data mining; entertainment; recommender systems; Maslow Hierarchy of Needs theory; collaborative filtering models; layered recommendation; movie promotion; movie recommendation; top-N strategy; user choice; user interest layered perspective; user interest mining; user need mining; user rating layered structure; user taste; Clustering algorithms; Collaboration; Educational institutions; Motion pictures; Prediction algorithms; Recommender systems; Vectors; Collaborative Filtering; Recommender System;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image and Signal Processing (CISP), 2014 7th International Congress on
Conference_Location :
Dalian
Type :
conf
DOI :
10.1109/CISP.2014.7003752
Filename :
7003752
Link To Document :
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