An Agent-based Customized Recommender System for Product and Service Family Design

This paper introduces an agent-based recommender system to support customized recommendations for product and service family design in electronic market environments. In this research, a preference learning mechanism is used to recommend appropriate products or services to customers and determine a...

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Bibliographic Details
Published inIISE Annual Conference. Proceedings p. 824
Main Authors Moon, Seung Ki, Simpson, Timothy W, Kumara, Soundar R T
Format Journal Article
LanguageEnglish
Published Norcross Institute of Industrial and Systems Engineers (IISE) 01.01.2007
Subjects
Algorithms
Customer services
Customization
Electronics industry
Expected values
Knowledge
Manufacturing
Market segments
Preferences
Product design
Product development
Recommender systems
Trends
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Summary:This paper introduces an agent-based recommender system to support customized recommendations for product and service family design in electronic market environments. In this research, a preference learning mechanism is used to recommend appropriate products or services to customers and determine a preference value for each market segment in the product or service family. We demonstrate the implementation of the proposed recommender system using a multi-agent framework. Through experiments, we illustrate that the proposed recommender system can be used for customized recommendation and market segment design in various electronic market environments. [PUBLICATION ABSTRACT]