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dc.date.accessioned 2012-07-13T12:16:49Z
dc.date.available 2012-07-13T12:16:49Z
dc.date.issued 2011
dc.identifier.uri http://sedici.unlp.edu.ar/handle/10915/18644
dc.description.abstract A fundamental challenge in personalized news recommendation is to account for the notion of trust. In this work we show how the notion of trust can be qualitatively modeled and incorporated into the architecture of a news recommendation system. The proposed system enables users to express explicit trust statements on news reports, news sources and other users. Trust is modeled and propagated using a dialectical process supported by a defeasible logic programming interpreter. We illustrate the operation of the system with some illustrative examples, describe the system architecture and discuss future steps. en
dc.format.extent 211-220 es
dc.language es es
dc.subject argumentation; news recommender systems; trust management es
dc.subject System architectures es
dc.subject Web-based services es
dc.title System architecture for trust-based news recommenders on the web en
dc.type Objeto de conferencia es
sedici.creator.person Briguez, Cristian E. es
sedici.creator.person Sagui, Fernando es
sedici.creator.person Capobianco, Marcela es
sedici.creator.person Maguitman, Ana Gabriela es
sedici.description.note Presentado en el XII Workshop Agentes y Sistemas Inteligentes (WASI) 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 2011-10
sedici.relation.event XVII Congreso Argentino de Ciencias de la Computación 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)