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.
