Discovering Imprecise Temporal Associations

T. Sudkamp; R. J. Hammell

doi:10.1109/NAFIPS.2003.1226763

Discovering Imprecise Temporal Associations

T. Sudkamp, R. J. Hammell

Computer Science and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	American English
Title of host publication	22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003
Editors	Ellen L. Walker
Publisher	IEEE
Pages	99-104
Number of pages	6
ISBN (Print)	0-7803-7918-7
DOIs	https://doi.org/10.1109/NAFIPS.2003.1226763
State	Published - 2003
Event	22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003 - Chicago, United States Duration: Jul 24 2003 → Jul 26 2003

Conference

Conference	22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003
Country/Territory	United States
City	Chicago
Period	7/24/03 → 7/26/03

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

Access to Document

10.1109/NAFIPS.2003.1226763License: Unspecified

Cite this

Sudkamp, T & Hammell, RJ 2003, Discovering Imprecise Temporal Associations. in EL Walker (ed.), 22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003., 1226763, IEEE, pp. 99-104, 22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003, Chicago, United States, 7/24/03. https://doi.org/10.1109/NAFIPS.2003.1226763

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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.",

keywords = "Algorithm design and analysis, Computer science, Data analysis, Data engineering, Data mining, Databases, Distributed computing, Fuzzy sets, Information analysis, Marine vehicles",

author = "T. Sudkamp and Hammell, \{R. J.\}",

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doi = "10.1109/NAFIPS.2003.1226763",

language = "American English",

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AB - 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.

KW - Algorithm design and analysis

KW - Computer science

KW - Data analysis

KW - Data engineering

KW - Data mining

KW - Databases

KW - Distributed computing

KW - Fuzzy sets

KW - Information analysis

KW - Marine vehicles

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BT - 22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003

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PB - IEEE

T2 - 22nd International Conference of the North American Fuzzy Information Processing Society, NAFIPS 2003

Y2 - 24 July 2003 through 26 July 2003

ER -

Discovering Imprecise Temporal Associations

Abstract

Conference

ASJC Scopus Subject Areas

Keywords

Disciplines

Access to Document

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