Discovering association patterns in large spatio-temporal databases

Eric M H Lee, Chun Chung Chan

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

7 Citations (Scopus)

Abstract

Over the past few years, a considerable number of studies have been made on market basket analysis. Market basket analysis is a useful method for discovering customer purchasing patterns by extracting association from stores' transaction databases. In many business of today, customer transactions can be made in many different geographical locations round the clock, especially after e-business have become prevalent. The traditional methods that consider only the association rules of an individual location or all locations as a whole are not suitable for such a multi-location environment. We design a novel and efficient algorithm for mining spatio-temporal association rules which have multi-level time and location granularities, in spatio-temporal databases. Experimental results have shown that our methods are efficient and we can find spatio-temporal association rules satisfactorily.
Original languageEnglish
Title of host publicationProceedings - ICDM Workshops 2006 - 6th IEEE International Conference on Data Mining - Workshops
Pages349-354
Number of pages6
Publication statusPublished - 1 Dec 2006
Event6th IEEE International Conference on Data Mining - Workshops, ICDM 2006 - Hong Kong, Hong Kong
Duration: 18 Dec 200618 Dec 2006

Conference

Conference6th IEEE International Conference on Data Mining - Workshops, ICDM 2006
Country/TerritoryHong Kong
CityHong Kong
Period18/12/0618/12/06

ASJC Scopus subject areas

  • Engineering(all)

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