Complex spatial relationships

Robert Munro*, Sanjay Chawla, Pei Sun

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

27 Citations (Scopus)

Abstract

This paper describes the need for mining complex relationships in spatial data. Complex relationships are defined as those involving two or more of: multi-feature colocation, self-colocation, one-to-many relationships, self-exclusion and multi-feature exclusion. We demonstrate that even in the mining of simple relationships, knowledge of complex relationships is necessary to accurately calculate the significance of results. We implement a representation of spatial data such that it contains known 'weak-monotonic' properties, which are exploited for the efficient mining of complex relationships, and discuss the strengths and limitations of this representation.

Original languageEnglish
Title of host publicationProceedings - 3rd IEEE International Conference on Data Mining, ICDM 2003
Pages227-234
Number of pages8
Publication statusPublished - 2003
Externally publishedYes
Event3rd IEEE International Conference on Data Mining, ICDM '03 - Melbourne, FL, United States
Duration: 19 Nov 200322 Nov 2003

Publication series

NameProceedings - IEEE International Conference on Data Mining, ICDM
ISSN (Print)1550-4786

Conference

Conference3rd IEEE International Conference on Data Mining, ICDM '03
Country/TerritoryUnited States
CityMelbourne, FL
Period19/11/0322/11/03

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