Title
Recommendations in a heterogeneous service environment
Abstract
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.
Year
DOI
Venue
2013
10.1007/s11042-011-0874-2
Multimedia Tools Appl.
Keywords
Field
DocType
Personalized television,Recommendations,Content-based,Collaborative filtering,Similarity,Media convergence,Personal Program Guide,DVB,YouTube
Digital video,Broadcasting,Collaborative filtering,Computer science,Filter (signal processing),Technological convergence,Digital Video Broadcasting,Multimedia
Journal
Volume
Issue
ISSN
62
3
1380-7501
Citations 
PageRank 
References 
1
0.34
12
Authors
6
Name
Order
Citations
PageRank
Christian Überall1101.62
Christopher Köhnen2112.00
Veselin Rakocevic319928.20
Rudolf Jäger4143.06
Erich Hoy510.34
Muttukrishnan Rajarajan659361.50