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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Add this copy of Towards Metadata-Aware Algorithms for Recommender to cart. $65.94, new condition, Sold by discount_scientific_books rated 3.0 out of 5 stars, ships from Sterling Heights, MI, UNITED STATES, published 2010 by Peter Lang Gmbh, Internationaler Verlag Der Wissenschaften.
Edition:
2010, Peter Lang Gmbh, Internationaler Verlag Der Wissenschaften
