A similarity inference method for reducing the cost of pair comparison

Muh-Cherng Wu*, Shih Ching Wu, Tai Chang Hsia, Shang Hwa Hsu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Group technology must group similar parts into families. In classifying parts based on their global shapes, the similarity of parts has to be manually measured by performing pair comparison. The cost of exhaustively performing pair comparison is quite high when the number of parts to be grouped is large. This paper proposes interval intersection, a novel similarity inference method that effectively infers the pair-comparison data from a set of known data. Justified by empirical experiments, the proposed method outperforms the previous methods when 31% or more of data is known.

Original languageEnglish
Pages (from-to)774-780
Number of pages7
JournalInternational Journal of Advanced Manufacturing Technology
Issue number7-8
StatePublished - 1 Jan 2006


  • Comparison
  • Group technology
  • Pair
  • Set intersection
  • Similarity inference

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