As recommender systems (RS) allow means of guiding consumers through the overloaded choices of products available, the recommendation problem has always been of great interest for both academic and industry. Metadata such as content information about the items (attributes) have typically been used to enrich RS algorithms. Recently, the trend of employing RS has expanded to other e-communities such as social tagging systems, inspiring the possibility to exploit tags to enhance RS. This book reports several research gaps in ...
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As recommender systems (RS) allow means of guiding consumers through the overloaded choices of products available, the recommendation problem has always been of great interest for both academic and industry. Metadata such as content information about the items (attributes) have typically been used to enrich RS algorithms. Recently, the trend of employing RS has expanded to other e-communities such as social tagging systems, inspiring the possibility to exploit tags to enhance RS. This book reports several research gaps in metadata-aware RS algorithms. In particular, it discusses attribute-aware RS algorithms focusing on the overlooked item prediction problem as well as the new emerging challenge of tag-aware RS algorithms.
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Publisher:
Peter Lang Gmbh, Internationaler Verlag Der Wissenschaften
Published:
2010
Language:
English
Alibris ID:
18147683108
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New. Sewn binding. Cloth over boards. 117 p. Contains: Illustrations. Informationstechnologie Und Oekonomie, 34. In Stock. 100% Money Back Guarantee. Brand New, Perfect Condition, allow 4-14 business days for standard shipping. To Alaska, Hawaii, U.S. protectorate, P.O. box, and APO/FPO addresses allow 4-28 business days for Standard shipping. No expedited shipping. All orders placed with expedited shipping will be cancelled. Over 3, 000, 000 happy customers.
