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dc.date.accessioned 2012-11-08T12:31:41Z
dc.date.available 2012-11-08T12:31:41Z
dc.date.issued 2006-08
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/23858
dc.description.abstract The success of personal information agents depends on their capacity to both identify relevant information for users and proactively recommend context-relevant information. In this paper, we propose an approach to enable proactive context-aware recommendation based on the knowledge of both user interests and browsing patterns. The pro- posed approach analyzes the browsing behavior of users to derive a semantically enhanced context that points out the information which is likely to be relevant for a user according to its current activities. en
dc.language en es
dc.subject Patterns es
dc.subject Information browsers es
dc.title Learning browsing patterns for context-aware recommendation en
dc.type Objeto de conferencia es
sedici.identifier.isbn 0-387-34654-6 es
sedici.creator.person Godoy, Daniela Lis es
sedici.creator.person Amandi, Analía es
sedici.description.note IFIP International Conference on Artificial Intelligence in Theory and Practice - Agents 1 es
sedici.subject.materias Ciencias Informáticas es
sedici.description.fulltext true es
mods.originInfo.place Red de Universidades con Carreras en Informática (RedUNCI) es
sedici.subtype Objeto de conferencia es
sedici.rights.license Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)
sedici.rights.uri http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
sedici.date.exposure 2006-08
sedici.relation.event 19 th IFIP World Computer Congress - WCC 2006 es
sedici.description.peerReview peer-review es


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Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) Excepto donde se diga explícitamente, este item se publica bajo la siguiente licencia Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)