Interpolation techniques for geo-spatial association rule mining

Dan Li, Jitender Deogun, Sherri Harms

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

Abstract

Association rule mining has become an important component of information processing systems due to significant increase in its applications. In this paper, our main objective is to find which interpolation approaches are best suited for discovering geo-spatial association rules from unsampled points. We investigate and integrate two interpolation approaches into our geo-spatial association rule mining algorithm. We call them pre-interpolation and post-interpolation approaches.

Original languageEnglish (US)
Title of host publicationRough Sets, Fuzzy Sets, Data Mining and Granular Computing - 9th International Conference, RSFDGrC 2003, Proceedings
EditorsGuoyin Wang, Qing Liu, Yiyu Yao, Andrzej Skowron
PublisherSpringer Verlag
Pages573-580
Number of pages8
ISBN (Print)3540140409, 9783540140405
DOIs
StatePublished - 2003
Event9th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, RSFDGrC 2003 - Chongqing, China
Duration: May 26 2003May 29 2003

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2639
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing, RSFDGrC 2003
Country/TerritoryChina
CityChongqing
Period5/26/035/29/03

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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