Recommendations in a heterogeneous service environment

被引:4
作者
Ueberall, Christian [1 ,2 ]
Koehnen, Christopher [1 ,2 ]
Rakocevic, Veselin [1 ]
Jaeger, Rudolf [2 ]
Hoy, Erich [2 ]
Rajarajan, Muttukrishnan [1 ]
机构
[1] City Univ London, London EC1V 0HB, England
[2] Univ Appl Sci, Tech Hsch Mittelhessen, D-61169 Friedberg, Germany
关键词
Personalized television; Recommendations; Content-based; Collaborative filtering; Similarity; Media convergence; Personal Program Guide; DVB; YouTube; ALGORITHMS;
D O I
10.1007/s11042-011-0874-2
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper presents novel algorithms which are able to generate recommendations within a heterogeneous service environment. In this work explicitly set preferences as well as implicitly logged viewing behavior are employed to generate recommendations for Digital Video Broadcast (DVB) content. This paper also discusses the similarity between the DVB genres and YouTube categories. In addition it presents results to show the comparison between well known collaborative filtering methods. The outcome of this comparison study is used to identify the most suitable filtering method to use in the proposed environment. Finally the paper presents a novel Personal Program Guide (PPG), which is used as a tool to visualize the generated recommendations within a heterogeneous service environment. This PPG is also capable of showing the linear DVB content and the non-linear YouTube videos in a single view.
引用
收藏
页码:785 / 820
页数:36
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