File(s) under permanent embargo
Aggregation functions for recommender systems
chapter
posted on 2015-01-01, 00:00 authored by Gleb BeliakovGleb Beliakov, T Calvo, Simon JamesSimon JamesThis 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.
History
Title of book
Recommender systems handbookChapter number
23Pagination
777 - 808Publisher
SpringerPlace of publication
New York, N.Y.Publisher DOI
ISBN-13
9781489976369Language
engPublication classification
B Book chapter; B1 Book chapterCopyright notice
2015, SpringerExtent
28Editor/Contributor(s)
F Ricci, L Rokach, B ShapiraUsage metrics
Categories
No categories selectedKeywords
Licence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC