Fuzzy connected-triple for predicting inter-variable correlation

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)


Identifying relationship between attribute variables from different data sources is an emerging field in data mining. However, currently there seldom exist effective methods designed for this particular problem. In this paper, a novel approach for inter-variable correlation prediction is proposed through the employment of the concept of connected-triple, and implemented with fuzzy logic. By the use of link strength measurements and fuzzy inference, the job of detecting similar or related variables can be accomplished via examining the link relation patterns. Comparative experimental investigations are carried out, demonstrating the potential of the proposed work in generating acceptable predicted results, while involving only simple computations
Original languageEnglish
Title of host publicationThe 17th UK Workshop on Computational Intelligence
PublisherSpringer Nature
ISBN (Electronic)9783319669397
ISBN (Print)9783319669380
Publication statusPublished - 05 Sept 2017
Event17th Annual UK Workshop on Computational Intelligence - Cardiff University, Cardiff, United Kingdom of Great Britain and Northern Ireland
Duration: 06 Sept 201708 Sept 2017

Publication series

NameAdvances in Intelligent Systems and Computing
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365


Conference17th Annual UK Workshop on Computational Intelligence
Abbreviated titleUKCI-2017
Country/TerritoryUnited Kingdom of Great Britain and Northern Ireland
Period06 Sept 201708 Sept 2017


  • connected-triple
  • fuzzy inference
  • link analysis


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