Interactive product catalogue with user preference tracking

Steven Sheng Uei Guan*, Yuan Sherng Tay

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

In the context of m-commerce, small screen size poses serious difficulty for users to browse effectively through a product catalogue, given the limited number of products that may be presented on-screen. Despite the availability of search engines, filters and recommender systems to aid users, these techniques focus on a narrow segment of product offering. The users are thus denied the opportunity to do a more expansive exploration of the products available. This paper describes a novel approach to overcome the constraints of small screen size. Through integration of a product catalogue with a recommender system, an adaptive system has been created that guides users through the process of product browsing. An original technique has been developed to cluster similar positive examples together to identify areas of interest of a user. The performance of this technique has been evaluated and the results proved to be promising.

Original languageEnglish
Pages (from-to)58-81
Number of pages24
JournalInternational Journal of Web and Grid Services
Volume3
Issue number1
DOIs
Publication statusPublished - 2007
Externally publishedYes

Keywords

  • Clustering
  • Genetic algorithm
  • Interactive catalogue
  • M-commerce

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