Aggregation functions for recommender systems Beliakov, Gleb, Calvo, Tomasa and James, Simon 2015, Aggregation functions for recommender systems. In Ricci, F., Rokach, L. and Shapira, B. (ed), Recommender systems handbook, Springer, New York, N.Y., pp.777-808, doi: 10.1007/978-1-4899-7637-6_23. Attached Files Name Description MIMEType Size Downloads Title Aggregation functions for recommender systems Author(s) Beliakov, Gleb orcid.org/0000-0002-9841-5292 Calvo, Tomasa James, Simon Title of book Recommender systems handbook Editor(s) Ricci, F. Rokach, L. Shapira, B. Publication date 2015 Chapter number 23 Total chapters 28 Start page 777 End page 808 Total pages 32 Publisher Springer Place of Publication New York, N.Y. Summary This chapter gives an overview of aggregation functions and their use in recommender systems. The classical weighted average lies at the heart of various recommendation mechanisms, often being employed to combine item feature scores or predict ratings from similar users. Some improvements to accuracy and robustness can be achieved by aggregating different measures of similarity or using an average of recommendations obtained through different techniques. Advances made in the theory of aggregation functions therefore have the potential to deliver increased performance to many recommender 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 9781489976369 9781489976376 Language eng DOI 10.1007/978-1-4899-7637-6_23 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 ERA Research output type B Book chapter Copyright notice ©2015, Springer Persistent URL http://hdl.handle.net/10536/DRO/DU:30082089 Document type: Book Chapter Collection: School of Information Technology Related Links Link Description Connect to Elements publication management system Go to link with your DU access privileges   Connect to published version Go to link with your DU access privileges   Publisher URL Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Thu, 10 Mar 2016, 14:29:19 EST Thu, 10 Mar 2016, 14:39:31 EST Fri, 11 Mar 2016, 08:55:13 EST Sat, 12 Mar 2016, 05:11:03 EST Mon, 04 Jul 2016, 10:13:14 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 3 times in Scopus Search Google Scholar Access Statistics: 101 Abstract Views, 3 File Downloads  -  Detailed Statistics Created: Fri, 11 Mar 2016, 08:55:13 EST

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