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Informed recommender: basing recommendations on consumer product reviews

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

IEEE

Author: Aciar, Silvana Vanesa
Zhang, Debbie
Simoff, Simeon
Debenham, John
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
Document access: http://hdl.handle.net/2072/63320
Language: eng
Publisher: IEEE
Rights: Tots els drets reservats
Subject: Béns de consum
Comerç electrònic
Mineria de dades
Consumer goods
Electronic commerce
Data mining
Title: Informed recommender: basing recommendations on consumer product reviews
Type: info:eu-repo/semantics/article
Repository: Recercat

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