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A New Evolutionary Approach to Recommender Systems

Title
A New Evolutionary Approach to Recommender Systems
Authors
Kim, HT[Kim, Hyun-Tae]An, JN[An, Jinung]Ahn, CW[Ahn, Chang Wook]
DGIST Authors
An, JN[An, Jinung]
Issue Date
2014-03
Citation
IEICE Transactions on Information and Systems, E97D(3), 622-625
Type
Article
Article Type
Article
Keywords
Content-Based FilteringData GroupingEvolutionary ApproachInformation ScienceInteractive Evolutionary ComputationRecommendation MethodsRecommender SystemsSoftware EngineeringUser&aposs PreferenceUser&aposs Preferences
ISSN
0916-8532
Abstract
In this paper, a new evolutionary approach to recommender systems is presented. The aim of this work is to develop a new recommendation method that effectively adapts and immediately responds to the user's preference. To this end, content-based filtering is judiciously utilized in conjunction with interactive evolutionary computation (IEC). Specifically, a fitness-based truncation selection and a feature-wise crossover are devised to make full use of desirable properties of promising items within the IEC framework. Moreover, to efficiently search for proper items, the content-based filtering is modified in cooperation with data grouping. The experimental results demonstrate the effectiveness of the proposed approach, compared with existing methods. Copyright © 2014 The Institute of Electronics, Information and Communication Engineers.
URI
http://hdl.handle.net/20.500.11750/1587
DOI
10.1587/transinf.E97.D.622
Publisher
IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG
Related Researcher
Files:
There are no files associated with this item.
Collection:
Convergence Research Center for Wellness1. Journal Articles


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