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

電機工程系

研究成果: 書籍/報告/會議論文中的章節 › 會議投稿 › 同行評審

摘要

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.

原文	English
主出版物標題	New Trends on System Sciences and Engineering - Proceedings of ICSSE 2015
編輯	Hamido Fujita, Shun-Feng Su
發行者	IOS Press BV
頁面	76-88
頁數	13
ISBN（電子）	9781614995210
DOIs	https://doi.org/10.3233/978-1-61499-522-7-76
出版狀態	Published - 2015
事件	International Conference on System Science and Engineering, ICSSE 2015 - Morioka, Japan 持續時間: 6 7月 2015 → 8 7月 2015

出版系列

名字	Frontiers in Artificial Intelligence and Applications
卷	276
ISSN（列印）	0922-6389
ISSN（電子）	1879-8314

Conference

Conference	International Conference on System Science and Engineering, ICSSE 2015
國家/地區	Japan
城市	Morioka
期間	6/07/15 → 8/07/15

文獻附註

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

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

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Link to publication in Scopus

引用此

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

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title = "Sliding Window Approach for Effective Mining of Transitional Patterns",

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.",

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Huang, YP, Zwane, TS, Dlamini, SM & Dlamini, MG 2015, Sliding Window Approach for Effective Mining of Transitional Patterns. 於 H Fujita & S-F Su (編輯), New Trends on System Sciences and Engineering - Proceedings of ICSSE 2015. Frontiers in Artificial Intelligence and Applications, 卷 276, IOS Press BV, 頁 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 等.
New Trends on System Sciences and Engineering - Proceedings of ICSSE 2015. 編輯 / Hamido Fujita; Shun-Feng Su. IOS Press BV, 2015. p. 76-88 (Frontiers in Artificial Intelligence and Applications; 卷 276).

研究成果: 書籍/報告/會議論文中的章節 › 會議投稿 › 同行評審

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AU - Dlamini, Mbuso Gerald

PY - 2015

Y1 - 2015

N2 - 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.

AB - 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.

KW - data mining

KW - significant milestone

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T2 - International Conference on System Science and Engineering, ICSSE 2015

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Sliding Window Approach for Effective Mining of Transitional Patterns

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