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|DOI (Digital Object Identifier) Link:||https://doi.org/10.1007/s11047-009-9126-z|
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In recent years evolutionary and immune-inspired approaches have been applied to content-based and collaborative filtering. These biologically inspired approaches are well suited to problems like profile adaptation in content-based filtering and rating sparsity in collaborative filtering, due to their distributed and dynamic characteristics. In this paper we introduce the relevant concepts and algorithms and review the state of the art in evolutionary and immune-inspired information filtering. Our intention is to promote the interplay between information filtering and biologically inspired computing and boost developments in this emerging interdisciplinary field.
|Item Type:||Journal Article|
|Copyright Holders:||2009 Springer Science+Business Media B.V.|
|Extra Information:||From the issue entitled "Special Issue "Artificial Immune Systems - ICARIS 2007" guest edited by Leandro Nunes de Castro, Jon Timmis, Helder Knidel and Fernando Von Zuben.Special Issue "State of the Art in Swarm Intelligence: Practice" guest edited by Eric Bonabeau, David Corne and Riccardo Poli."
|Keywords:||genetic algorithms; artificial immune systems; information filtering|
|Academic Unit/Department:||Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
|Interdisciplinary Research Centre:||Centre for Research in Computing (CRC)|
|Depositing User:||Catherine McNulty|
|Date Deposited:||02 Feb 2011 10:51|
|Last Modified:||08 Oct 2016 07:18|
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