AVATAR:: An advanced multi-agent recommender system of personalized TV contents by semantic reasoning

被引：0

作者：

Blanco-Fernández, Y ^{[1
]}

Pazos-Arias, JJ ^{[1
]}

Gil-Solla, A ^{[1
]}

Ramos-Cabrer, M ^{[1
]}

Barragáns-Martínez, B ^{[1
]}

López-Nores, M ^{[1
]}

García-Duque, J ^{[1
]}

Fernández-Vilas, A ^{[1
]}

Dfaz-Redondo, RP ^{[1
]}

机构：

[1] Univ Vigo, Dept Telemat Engn, Vigo 36310, Spain

来源：

WEB INFORMATION SYSTEMS - WISE 2004, PROCEEDINGS | 2004年 / 3306卷

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper a recommender system of personalized TV contents. named AVATAR(1), 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.

引用

页码：415 / 421

页数：7

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