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Also published online by CEUR Workshop Proceedings (CEUR-WS.org, ISSN 1613-0073) In recent years there has been an increasing research interest
in novelty/diversity detection in Information Retrieval and
in Recommendation Systems. We propose a model that increases
the novelty of recommendations using a context user
profile that was created automatically using self-organizing
maps. Our system was evaluated on the Reuters Corpus
Volume 1 and our experiments show that filtering the recommended
items using a novelty score derived from the contextbased
user profile provides better search results in terms of
novel information that is presented to the user.This work was supported by the Ministerio de Educaci on y
Ciencia under the grant N. TIN2011-28538-C02, Novelty, di-
versity, context and time: newdimensions in next-generation
information retrieval and recommender systems
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