Aggregation of preferences in recommender systems

Beliakov, Gleb, Calvo, Tomasa and James, Simon 2011, Aggregation of preferences in recommender systems, in Recommender systems handbook, Springer, New York, pp.705-734.

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Title Aggregation of preferences in recommender systems
Author(s) Beliakov, Gleb
Calvo, Tomasa
James, Simon
Title of book Recommender systems handbook
Editor(s) Ricci, Francesco
Rokach, Lior
Shapira, Bracha
Kantor, Paul B.
Publication date 2011
Chapter number 22
Total chapters 25
Start page 705
End page 734
Total pages 30
Publisher Springer
Place of Publication New York
Keyword(s) preferences
recommender systems
Summary This chapter gives an overview of aggregation functions toward their use in recommender systems. Simple aggregation functions such as the arithmetic mean are often employed to aggregate user features, item ratings, measures of similarity, etc., however many other aggregation functions exist which could deliver increased accuracy and flexibility to many systems. We provide definitions of some important families and properties, sophisticated methods of construction, and various examples of aggregation functions in the domain of recommender systems.
ISBN 0387858199
9780387858197
Edition 1st
Language eng
Field of Research 080108 Neural, Evolutionary and Fuzzy Computation
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category B1 Book chapter
HERDC collection year 2011
Copyright notice ©2011, Springer
Persistent URL http://hdl.handle.net/10536/DRO/DU:30045337

Document type: Book Chapter
Collection: School of Information Technology
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