News@hand: A semantic web approach to recommending news
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News@hand: A semantic web approach to recommending news
Title:
News@hand: A semantic web approach to recommending news
Author:
Cantador, Iván; Bellogín, Alejandro; Castells, Pablo
Entity:
UAM. Departamento de Ingeniería Informática
UAM Author:
Cantador Gutiérrez, Iván
; Castells Azpilicueta, Pablo
; Castells Azpilicueta, Pablo
Publisher:
Springer Berlin Heidelberg
Date:
2008
Citation:
Adaptive Hypermedia and Adaptive Web-Based Systems: 5th International Conference, AH 2008, Hannover, Germany, July 29 - August 1, 2008. Proceedings. Lecture Notes in Computer Science, Volumen 5149. Springer, 2008. 279-283.
ISSN:
0302-9743 (print); 1611-3349 (online)
ISBN:
978-3-540-70984-8 (print); 978-3-540-70987-9 (online)
DOI:
10.1007/978-3-540-70987-9_34
Funded by:
This research was supported by the European Commission (FP6-027685-MESH) and
the Spanish Ministry of Science and Education (TIN2005-06885). The expressed
content is the view of the authors but not necessarily the view of the MESH project as
a whole
Project:
info:eu-repo/grantAgreement/EC/FP6/027685
Editor's Version:
http://dx.doi.org/10.1007/978-3-540-70987-9_34
Subjects:
Group modelling; Ontologies; Personalisation; Recommender systems; Semantic web; User modelling; Informática
Note:
The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-540-70987-9_34
Proceedings of 5th International Conference, AH 2008, Hannover, Germany, July 29 - August 1, 2008.
Proceedings of 5th International Conference, AH 2008, Hannover, Germany, July 29 - August 1, 2008.
Rights:
© Springer-Verlag Berlin Heidelberg 2008
Abstract:
We present News@hand, a news recommender system which applies semantic-based technologies to describe and relate news contents and user preferences in order to produce enhanced recommendations. The exploitation of conceptual information describing contents and user profiles, along with the capability of inferring knowledge from the semantic relations defined in the ontologies, enabling different content-based collaborative recommendation models, are the key distinctive aspects of the system. The multi-domain portability, the multi-media source applicability, and addressing of some limitations of current recommender systems are the main benefits of our proposed approach.
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™ Scholar:
Cantador, Iván
-
Bellogín, Alejandro
-
Castells, Pablo