A comparison of audiovisual content recommender systems performance: Collaborative vs. semantic approaches

Author

Sotelo, Rafael ; Juayek, Marcos ; Scuoteguazza, Alejandra

Author_Institution

Fac. de Ing., Univ. de Montevideo, Montevideo, Uruguay

fYear

2013

fDate

5-7 June 2013

Firstpage

1

Lastpage

5

Abstract

In this paper we compare the efficiency of the semantic approach with the traditional collaborative filtering in recommender systems applied to the field of audiovisual contents. We use actual data from MovieLens database to train the recommenders´ algorithms and to compare results. An ontology for the audiovisual content was developed importing data from IMDB. For the sake of reproducibility the novel LensKit platform has been utilized.

Keywords

audio-visual systems; collaborative filtering; digital television; ontologies (artificial intelligence); recommender systems; telecommunication computing; LensKit platform; MovieLens database; audiovisual content recommender system performance; audiovisual contents; collaborative approach; ontology; recommender algorithm; semantic approach; traditional collaborative filtering; Collaboration; Motion pictures; Ontologies; Recommender systems; Semantics; TV; Collaborative filtering; Ontology; Recommender systems performance; Semantic filtering;

fLanguage

English

Publisher

ieee

Conference_Titel

Broadband Multimedia Systems and Broadcasting (BMSB), 2013 IEEE International Symposium on

Conference_Location

London

ISSN

2155-5044

Type

conf

DOI

10.1109/BMSB.2013.6621791

Filename

6621791