Soft Concept Hierarchies to Summarise Data Streams and Highlight Anomalous Changes

Trevor P Martin; Y Shen; A Majidian

doi:10.1007/978-3-642-14058-7_5

Soft Concept Hierarchies to Summarise Data Streams and Highlight Anomalous Changes

Trevor P Martin, Y Shen, A Majidian

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

4 Citations (Scopus)

Abstract

A hierarchical approach is natural when managing large volumes of information, from both static (database) and dynamic (datastream) sources. Hierarchies allow progressively finer division into more specific categories, but frequently the categories are fuzzy rather than crisp. In this paper, we use fuzzy formal concept analysis to extract soft hierarchies from data. The hierarchies are used to classify data and to monitor changes over time by means of a fuzzy confidence measure for association analysis. A (simulated) stream of terrorism incident data is used as proof of concept.

Translated title of the contribution	Soft Concept Hierarchies to Summarise Data Streams and Highlight Anomalous Changes
Original language	English
Title of host publication	Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications
Subtitle of host publication	13th International Conference, IPMU 2010, Dortmund, Germany, June 28–July 2, 2010. Proceedings, Part II
Editors	Eyke Hüllermeier, Rudolf Kruse, Frank Hoffmann
Publisher	Springer
Pages	44-54
Number of pages	11
ISBN (Electronic)	9783642140587
ISBN (Print)	9783642140570
DOIs	https://doi.org/10.1007/978-3-642-14058-7_5
Publication status	Published - 29 Jun 2010

Publication series

Name	Communications in Computer and Information Science
Publisher	Springer
Volume	81
ISSN (Print)	1865-0929

Keywords

fuzzy formal concept hierarchies
fuzzy association rules
fuzzy confidence
dynamic data streams

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/978-3-642-14058-7_5

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Martin, T. P., Shen, Y., & Majidian, A. (2010). Soft Concept Hierarchies to Summarise Data Streams and Highlight Anomalous Changes. In E. Hüllermeier, R. Kruse, & F. Hoffmann (Eds.), Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications: 13th International Conference, IPMU 2010, Dortmund, Germany, June 28–July 2, 2010. Proceedings, Part II (pp. 44-54). (Communications in Computer and Information Science; Vol. 81). Springer. https://doi.org/10.1007/978-3-642-14058-7_5

Martin, Trevor P ; Shen, Y ; Majidian, A. / Soft Concept Hierarchies to Summarise Data Streams and Highlight Anomalous Changes. Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications: 13th International Conference, IPMU 2010, Dortmund, Germany, June 28–July 2, 2010. Proceedings, Part II. editor / Eyke Hüllermeier ; Rudolf Kruse ; Frank Hoffmann. Springer, 2010. pp. 44-54 (Communications in Computer and Information Science).

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abstract = "A hierarchical approach is natural when managing large volumes of information, from both static (database) and dynamic (datastream) sources. Hierarchies allow progressively finer division into more specific categories, but frequently the categories are fuzzy rather than crisp. In this paper, we use fuzzy formal concept analysis to extract soft hierarchies from data. The hierarchies are used to classify data and to monitor changes over time by means of a fuzzy confidence measure for association analysis. A (simulated) stream of terrorism incident data is used as proof of concept.",

keywords = "fuzzy formal concept hierarchies, fuzzy association rules, fuzzy confidence, dynamic data streams",

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Martin, TP, Shen, Y & Majidian, A 2010, Soft Concept Hierarchies to Summarise Data Streams and Highlight Anomalous Changes. in E Hüllermeier, R Kruse & F Hoffmann (eds), Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications: 13th International Conference, IPMU 2010, Dortmund, Germany, June 28–July 2, 2010. Proceedings, Part II. Communications in Computer and Information Science, vol. 81, Springer, pp. 44-54. https://doi.org/10.1007/978-3-642-14058-7_5

Soft Concept Hierarchies to Summarise Data Streams and Highlight Anomalous Changes. / Martin, Trevor P; Shen, Y; Majidian, A.
Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications: 13th International Conference, IPMU 2010, Dortmund, Germany, June 28–July 2, 2010. Proceedings, Part II. ed. / Eyke Hüllermeier; Rudolf Kruse; Frank Hoffmann. Springer, 2010. p. 44-54 (Communications in Computer and Information Science; Vol. 81).

Research output: Chapter in Book/Report/Conference proceeding › Conference Contribution (Conference Proceeding)

TY - GEN

T1 - Soft Concept Hierarchies to Summarise Data Streams and Highlight Anomalous Changes

AU - Martin, Trevor P

AU - Shen, Y

AU - Majidian, A

PY - 2010/6/29

Y1 - 2010/6/29

N2 - A hierarchical approach is natural when managing large volumes of information, from both static (database) and dynamic (datastream) sources. Hierarchies allow progressively finer division into more specific categories, but frequently the categories are fuzzy rather than crisp. In this paper, we use fuzzy formal concept analysis to extract soft hierarchies from data. The hierarchies are used to classify data and to monitor changes over time by means of a fuzzy confidence measure for association analysis. A (simulated) stream of terrorism incident data is used as proof of concept.

AB - A hierarchical approach is natural when managing large volumes of information, from both static (database) and dynamic (datastream) sources. Hierarchies allow progressively finer division into more specific categories, but frequently the categories are fuzzy rather than crisp. In this paper, we use fuzzy formal concept analysis to extract soft hierarchies from data. The hierarchies are used to classify data and to monitor changes over time by means of a fuzzy confidence measure for association analysis. A (simulated) stream of terrorism incident data is used as proof of concept.

KW - fuzzy formal concept hierarchies

KW - fuzzy association rules

KW - fuzzy confidence

KW - dynamic data streams

U2 - 10.1007/978-3-642-14058-7_5

DO - 10.1007/978-3-642-14058-7_5

M3 - Conference Contribution (Conference Proceeding)

SN - 9783642140570

T3 - Communications in Computer and Information Science

SP - 44

EP - 54

BT - Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications

A2 - Hüllermeier, Eyke

A2 - Kruse, Rudolf

A2 - Hoffmann, Frank

PB - Springer

ER -

Martin TP, Shen Y, Majidian A. Soft Concept Hierarchies to Summarise Data Streams and Highlight Anomalous Changes. In Hüllermeier E, Kruse R, Hoffmann F, editors, Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications: 13th International Conference, IPMU 2010, Dortmund, Germany, June 28–July 2, 2010. Proceedings, Part II. Springer. 2010. p. 44-54. (Communications in Computer and Information Science). doi: 10.1007/978-3-642-14058-7_5

Soft Concept Hierarchies to Summarise Data Streams and Highlight Anomalous Changes

Abstract

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Keywords

UN SDGs

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