Discovering Imprecise Temporal Associations

T. Sudkamp, R. J. Hammell

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

Abstract

This paper examines the discovery of associations defined by fuzzy temporal predicates in time-tagged information from multiple distributed data sources. The use of fuzzy predicates provides the ability to represent and analyze imprecise temporal relation-ships, including temporal ordering and duration. In particular, we are concerned with the adaptability of common data mining strategies to relations defined by fuzzy temporal predicates.

Original languageAmerican English
Title of host publication22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003
EditorsEllen L. Walker
PublisherIEEE
Pages99-104
Number of pages6
ISBN (Print)0-7803-7918-7
DOIs
StatePublished - 2003
Event22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003 - Chicago, United States
Duration: Jul 24 2003Jul 26 2003

Conference

Conference22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003
Country/TerritoryUnited States
CityChicago
Period7/24/037/26/03

ASJC Scopus Subject Areas

  • General Computer Science
  • General Mathematics

Keywords

  • Algorithm design and analysis
  • Computer science
  • Data analysis
  • Data engineering
  • Data mining
  • Databases
  • Distributed computing
  • Fuzzy sets
  • Information analysis
  • Marine vehicles

Disciplines

  • Computer Sciences
  • Engineering
  • Mathematics

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