Supporting retrieval of configurable goods based on statistical analysis of combination constraints

Takayuki Shiga*, Mizuho Iwaihara, Yahiko Kambayashi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)


Configurable goods are becoming a popular style for e-commerce web shopping sites in which buyers can configure a product of their needs from menus listing components. In this paper, we propose a sophisticated system support for designing web menus for configurable goods. We discuss evaluating the correlations between component classes of configurable goods. Such correlations can be used to design web menus which cause fewer trial errors and give an aggregated view of product constraints. Choosing a proper quantitative measure for correlation is an important issue here. We compare a number of statistical and mining methods by experiments and show that Cramer's coefficient is most suitable for this problem. Then we present an algorithm which generates a tree structure for web menus such that closely correlated component classes are clustered, and hence users can easily select components.

Original languageEnglish
Pages (from-to)12-22
Number of pages11
JournalSystems and Computers in Japan
Issue number2
Publication statusPublished - 2005 Feb
Externally publishedYes


  • Configurable goods
  • Data mining
  • E-commerce
  • Information retrieval

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Hardware and Architecture
  • Computational Theory and Mathematics


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