Recommender System Based 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	2006
dc.date.accessioned	2010-06-09T01:55:17Z
dc.date.available	2010-06-09T01:55:17Z
dc.date.issued	2010-06-09T01:55:17Z
dc.identifier.citation	Aciar, S., Zhang, D., Simoff, S., i Debenham, J. (2006). Recommender System Based on Consumer Product Reviews. IEEE/WIC/ACM International Conference on Web Intelligence : 2006 : WI 2006, 719-723. Recuperat 08 juny 2010, a http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4061458
dc.identifier.citation	0-7695-2747-7
dc.identifier.uri	http://hdl.handle.net/10256/2555
dc.format	application/pdf
dc.language.iso	eng
dc.publisher	IEEE
dc.relation	http://dx.doi.org/10.1109/WI.2006.144
dc.relation	© IEEE/WIC/ACM International Conference on Web Intelligence : 2006 : WI 2006, 2006, p. 719-723
dc.relation	Articles publicats (D-EEEiA)
dc.rights	Tots els drets reservats
dc.subject	Béns de consum
dc.subject	Comerç electrònic
dc.subject	Consumidors -- Conducta
dc.subject	Mineria de dades
dc.subject	Sistemes experts (Informàtica)
dc.subject	Consumer goods
dc.subject	Consumer behavior
dc.subject	Data mining
dc.subject	Electronic commerce
dc.subject	Expert systems (Computer science)
dc.title	Recommender System Based on Consumer Product Reviews
dc.type	info:eu-repo/semantics/article
dc.description.abstract	Consumer reviews, opinions and shared experiences in the use of a product is a powerful source of information about consumer preferences that can be used in recommender systems. Despite the importance and value of such information, there is no comprehensive mechanism that formalizes the opinions selection and retrieval process and the utilization of retrieved opinions due to the difficulty of extracting information from text data. In this paper, a new recommender system that is built on consumer product reviews is proposed. A prioritizing mechanism is developed for the system. The proposed approach is illustrated using the case study of a recommender system for digital cameras

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