A multi-agent system for recommending customized families of products

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Electronic markets and web-based content have improved traditional product development processes by increasing the participation of customers and applying various recommender systems to satisfy individual customer needs. This chapter introduces a multi-agent system to support customized producfamily design by recommending customers' preferences in dynamic electronic market environmentsIn the proposed system, a market-based learning mechanism is applied to determine the customerspreferences for recommending appropriate products to customers in the product family. The authors demonstrate the implementation of the proposed recommender system using a multi-agent frameworkThrough experiments, they illustrate that the proposed recommender system can determine the preference values of products for customized recommendation and market segment design in various electronic market environments.

Original languageEnglish (US)
Title of host publicationMass Customization for Personalized Communication Environments
Subtitle of host publicationIntegrating Human Factors
PublisherIGI Global
Pages35-48
Number of pages14
ISBN (Print)9781605662602
DOIs
StatePublished - Dec 1 2009

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Social Sciences(all)

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    Moon, S. K., Simpson, T. W., & Kumara, S. R. T. (2009). A multi-agent system for recommending customized families of products. In Mass Customization for Personalized Communication Environments: Integrating Human Factors (pp. 35-48). IGI Global. https://doi.org/10.4018/978-1-60566-260-2.ch004