Informed recommender: basing recommendations on consumer product reviews

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dc.contributor.author Aciar, Silvana Vanesa
dc.contributor.author Zhang, Debbie
dc.contributor.author Simoff, Simeon
dc.contributor.author Debenham, John
dc.date.issued 2007
dc.identifier.citation Aciar, S., Zhang, D., Simoff, S., i Debenham, J. (2007). Informed Recommender: Basing Recommendations on Consumer Product Reviews. IEEE Intelligent Systems, 22, 3, 39-47. Recuperat 08 juny 2010, a http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4216979
dc.identifier.issn 1541-1672
dc.identifier.uri http://hdl.handle.net/10256/2554
dc.description.abstract Recommender systems attempt to predict items in which a user might be interested, given some information about the user's and items' profiles. Most existing recommender systems use content-based or collaborative filtering methods or hybrid methods that combine both techniques (see the sidebar for more details). We created Informed Recommender to address the problem of using consumer opinion about products, expressed online in free-form text, to generate product recommendations. Informed recommender uses prioritized consumer product reviews to make recommendations. Using text-mining techniques, it maps each piece of each review comment automatically into an ontology
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher IEEE
dc.relation.isformatof Reproducció digital del document publicat a: http://dx.doi.org/10.1109/MIS.2007.55
dc.relation.ispartof © IEEE Intelligent Systems, 2007, vol. 22, p. 39-47
dc.relation.ispartofseries Articles publicats (D-EEEiA)
dc.rights Tots els drets reservats
dc.subject Béns de consum
dc.subject Comerç electrònic
dc.subject Mineria de dades
dc.subject Consumer goods
dc.subject Electronic commerce
dc.subject Data mining
dc.title Informed recommender: basing recommendations on consumer product reviews
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1109/MIS.2007.55


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