TV Program Search and Recommendation Based on TV and Viewer Ontologies

Author

Jung-Min Kim ; PanSeop Shin ; Hyun-Sook Chung

Author_Institution

Dept. of Comput. Eng., Daejin Univ., Pocheon, South Korea

fYear

2013

fDate

24-26 June 2013

Firstpage

1

Lastpage

4

Abstract

In this paper we propose a searching and recommendation method of TV program contents based on TV contents and viewers ontologies by performing TV program usage examination, ontology matching, and recommendation processes. Our scheme searches TV programs by computing the similarity between contents ontologies, filter the candidates with preferences of viewers, and return the list of top-N ranked program contents. From the experimental results, we know that our scheme yields about 80% of average precision for 53 documentary programs.

Keywords

IPTV; content-based retrieval; information filtering; ontologies (artificial intelligence); recommender systems; TV program content recommendation method; TV program content searching method; TV program usage examination; average precision; content ontology similarity measurement; content-based filtering; documentary programs; recommendation processes; top-N ranked program content list; viewer ontology matching; viewer preferences; Animals; Broadcasting; Computational modeling; Filtering; Ontologies; TV; Vectors;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Science and Applications (ICISA), 2013 International Conference on

Conference_Location

Suwon

Print_ISBN

978-1-4799-0602-4

Type

conf

DOI

10.1109/ICISA.2013.6579484

Filename

6579484