Movie Genres Classification using Collaborative Filtering

被引：0
|
作者：
Ghawi, Raji [1 ]
Pfeffer, Juergen [1 ]
机构：
[1] Tech Univ Munich, Bavarian Sch Publ Policy, Munich, Germany
来源：
IIWAS2019: THE 21ST INTERNATIONAL CONFERENCE ON INFORMATION INTEGRATION AND WEB-BASED APPLICATIONS & SERVICES | 2019年
关键词：
movie genres classification; collaborative filtering; multi-label classification; KNN; networks; FEATURES;
D O I：
10.1145/3366030.3366034
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
In this paper, we present an approach for classifying movie genres based on user-ratings. Our approach is based on collaborative filtering (CF), a common technique used in recommendation systems, where the similarity between movies based on user-ratings, is used to predict the genres of movies. The results of conducted experiments show that our genres classification approach outperforms many existing approaches, by achieving an F1-score of 0.70, and a hit-rate of 94%.
引用
收藏
页码：35 / 44
页数：10
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