A framework for visualizing association mining results

Gürdal Ertek, Ayhan Demiriz

Research output: Chapter in Book/Report/Conference proceedingConference contribution

26 Citations (Scopus)

Abstract

Association mining is one of the most used data mining techniques due to interpretable and actionable results. In this study we propose a framework to visualize the association mining results, specifically frequent itemsets and association rules, as graphs. We demonstrate the applicability and usefulness of our approach through a Market Basket Analysis (MBA) case study where we visually explore the data mining results for a supermarket data set. In this case study we derive several interesting insights regarding the relationships among the items and suggest how they can be used as basis for decision making in retailing.

Original languageEnglish
Title of host publicationComputer and Information Sciences - ISCIS 2006
Subtitle of host publication21th International Symposium, Proceedings
PublisherSpringer Verlag
Pages593-602
Number of pages10
ISBN (Print)3540472428, 9783540472421
DOIs
Publication statusPublished - 2006
Externally publishedYes
EventISCIS 2006: 21th International Symposium on Computer and Information Sciences - Istanbul, Turkey
Duration: Nov 1 2006Nov 3 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4263 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceISCIS 2006: 21th International Symposium on Computer and Information Sciences
Country/TerritoryTurkey
CityIstanbul
Period11/1/0611/3/06

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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