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

页码：35 / 44

页数：10

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