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AVATAR: An Advanced Multi-agent Recommender System of Personalized TV Contents by Semantic Reasoning

by: Yolanda Blanco-Fernández, José J. Pazos-Arias, Alberto Gil-Solla, Manuel Ramos-Cabrer, Belén Barragáns-Martínez, Martín López-Nores, Jorge García-Duque, Ana Fernández-Vilas, and Rebeca P. Díaz-Redondo

In: Lecture Notes Computer Science, Nr. 3306 (2004) , p. 415--421.

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URL:	http://www.springerlink.com/content/umwe9p9rp4h1hjev

In this paper a recommender system of personalized TV contents, named AVATARWork supported by the Ministerio de Educación y Ciencia Research Project TSI2004-03677., is presented. We propose a modular multi-agent architecture for the system, whose main novelty is the semantic reasoning about user preferences and historical logs, to improve the traditional syntactic content search. Our approach uses Semantic Web technologies – more specifically an OWL ontology – and the TV-Anytime standard to describe the TV contents. To reason about the ontology, we have defined a query language, named LIKO, for inferring knowledge from properties contained in it. In addition, we show an example of a semantic recommendation by means of some LIKO operators. ER -

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SpringerLink - Buchkapitel

BibTeX record

@article{BlaPazGil+04,
  abstract = {In this paper a recommender system of personalized TV contents, named AVATARWork supported by the Ministerio de Educación y Ciencia Research Project TSI2004-03677., is presented. We propose a modular multi-agent architecture for the system, whose main novelty is the semantic reasoning about user preferences and historical logs, to improve the traditional syntactic content search. Our approach uses Semantic Web technologies – more specifically an OWL ontology – and the TV-Anytime standard to describe the TV contents. To reason about the ontology, we have defined a query language, named LIKO, for inferring knowledge from properties contained in it. In addition, we show an example of a semantic recommendation by means of some LIKO operators.
ER  -},
  added-at = {2010-03-17T15:41:32.000+0100},
  author = {Blanco-Fernández, Yolanda and Pazos-Arias, José J. and Gil-Solla, Alberto and Ramos-Cabrer, Manuel and Barragáns-Martínez, Belén and López-Nores, Martín and García-Duque, Jorge and Fernández-Vilas, Ana and Díaz-Redondo, Rebeca P.},
  biburl = {http://www.bibsonomy.org/bibtex/2ef9a0aa85578c26ed81fd657042b8b3c/datentaste},
  description = {SpringerLink - Buchkapitel},
  interhash = {6e189130e59abb825659efc965404830},
  intrahash = {ef9a0aa85578c26ed81fd657042b8b3c},
  journal = {Lecture Notes Computer Science },
  keywords = {hpi_ism10 recomender},
  note = {(Web Information Systems – WISE 2004)},
  number = 3306,
  pages = {415--421},
  timestamp = {2010-03-17T15:41:32.000+0100},
  title = {AVATAR: An Advanced Multi-agent Recommender System of Personalized TV Contents by Semantic Reasoning},
  url = {http://www.springerlink.com/content/umwe9p9rp4h1hjev},
  year = 2004
}

Endnote record

%0 Journal Article
%1 BlaPazGil+04
%A Blanco-Fernández, Yolanda
%A Pazos-Arias, José J.
%A Gil-Solla, Alberto
%A Ramos-Cabrer, Manuel
%A Barragáns-Martínez, Belén
%A López-Nores, Martín
%A García-Duque, Jorge
%A Fernández-Vilas, Ana
%A Díaz-Redondo, Rebeca P.
%D 2004
%J Lecture Notes Computer Science 
%K 
%N 3306
%P 415--421
%T AVATAR: An Advanced Multi-agent Recommender System of Personalized TV Contents by Semantic Reasoning
%U http://www.springerlink.com/content/umwe9p9rp4h1hjev
%X In this paper a recommender system of personalized TV contents, named AVATARWork supported by the Ministerio de Educación y Ciencia Research Project TSI2004-03677., is presented. We propose a modular multi-agent architecture for the system, whose main novelty is the semantic reasoning about user preferences and historical logs, to improve the traditional syntactic content search. Our approach uses Semantic Web technologies – more specifically an OWL ontology – and the TV-Anytime standard to describe the TV contents. To reason about the ontology, we have defined a query language, named LIKO, for inferring knowledge from properties contained in it. In addition, we show an example of a semantic recommendation by means of some LIKO operators.
ER  -