Sliding Window Approach for Effective Mining of Transitional Patterns

Yo Ping Huang; Thanduxolo Shannon Zwane; Siphamandla Musa Dlamini; Mbuso Gerald Dlamini

doi:10.3233/978-1-61499-522-7-76

Sliding Window Approach for Effective Mining of Transitional Patterns

Yo Ping Huang
, Thanduxolo Shannon Zwane
, Siphamandla Musa Dlamini
, Mbuso Gerald Dlamini

Department of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Frequent pattern mining research has raised an interest in studying the dynamic behavior of patterns whose frequency significantly alters over time periods. This paper presents an investigation into using a sliding window approach in exploring the dynamic behavior of frequent patterns in consecutive time periods where they occur in a data set. This approach gives a promising alternative to the existing techniques being used for decision makers to know the exact period in which a pattern's frequency significantly alters and therefore responds appropriately. The results will help in detecting and reporting significant changes in the frequency of patterns sequentially from one time period to another.

Original language	English
Title of host publication	New Trends on System Sciences and Engineering - Proceedings of ICSSE 2015
Editors	Hamido Fujita, Shun-Feng Su
Publisher	IOS Press BV
Pages	76-88
Number of pages	13
ISBN (Electronic)	9781614995210
DOIs	https://doi.org/10.3233/978-1-61499-522-7-76
State	Published - 2015
Event	International Conference on System Science and Engineering, ICSSE 2015 - Morioka, Japan Duration: 6 Jul 2015 → 8 Jul 2015

Publication series

Name	Frontiers in Artificial Intelligence and Applications
Volume	276
ISSN (Print)	0922-6389
ISSN (Electronic)	1879-8314

Conference

Conference	International Conference on System Science and Engineering, ICSSE 2015
Country/Territory	Japan
City	Morioka
Period	6/07/15 → 8/07/15

Bibliographical note

Publisher Copyright:
© 2015 The authors and IOS Press. All rights reserved.

Keywords

data mining
significant milestone
transitional patterns

Access to Document

10.3233/978-1-61499-522-7-76

Cite this

Huang, Y. P., Zwane, T. S., Dlamini, S. M., & Dlamini, M. G. (2015). Sliding Window Approach for Effective Mining of Transitional Patterns. In H. Fujita, & S.-F. Su (Eds.), New Trends on System Sciences and Engineering - Proceedings of ICSSE 2015 (pp. 76-88). (Frontiers in Artificial Intelligence and Applications; Vol. 276). IOS Press BV. https://doi.org/10.3233/978-1-61499-522-7-76

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Huang, YP, Zwane, TS, Dlamini, SM & Dlamini, MG 2015, Sliding Window Approach for Effective Mining of Transitional Patterns. in H Fujita & S-F Su (eds), New Trends on System Sciences and Engineering - Proceedings of ICSSE 2015. Frontiers in Artificial Intelligence and Applications, vol. 276, IOS Press BV, pp. 76-88, International Conference on System Science and Engineering, ICSSE 2015, Morioka, Japan, 6/07/15. https://doi.org/10.3233/978-1-61499-522-7-76

Sliding Window Approach for Effective Mining of Transitional Patterns. / Huang, Yo Ping; Zwane, Thanduxolo Shannon; Dlamini, Siphamandla Musa et al.
New Trends on System Sciences and Engineering - Proceedings of ICSSE 2015. ed. / Hamido Fujita; Shun-Feng Su. IOS Press BV, 2015. p. 76-88 (Frontiers in Artificial Intelligence and Applications; Vol. 276).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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Sliding Window Approach for Effective Mining of Transitional Patterns

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Keywords

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