EFP-M2 : efficient model for mining frequent patterns in transactional database

Herawan, Tutut, Noraziah, A., Abdullah, Zailani, Deris, Mustafa Mat and Abawajy, Jemal H. 2012, EFP-M2 : efficient model for mining frequent patterns in transactional database, in Computational collective intelligence : technologies and applications : 4th international conference, ICCCI 2012, Ho Chi Minh City, Vietnam, November 28-30, 2012 : proceedings, Springer Berlin Heidelberg, Berlin, Germany, pp.29-38.

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Title EFP-M2 : efficient model for mining frequent patterns in transactional database
Author(s) Herawan, Tutut
Noraziah, A.
Abdullah, Zailani
Deris, Mustafa Mat
Abawajy, Jemal H.
Title of book Computational collective intelligence : technologies and applications : 4th international conference, ICCCI 2012, Ho Chi Minh City, Vietnam, November 28-30, 2012 : proceedings
Editor(s) Nguyen, Ngoc-Thanh
Hoang, Kiem
Jedrzejowicz, Piotr
Publication date 2012
Series Lecture notes in artificial intelligence; Lecture notes in computer science, v7654
Chapter number 4
Total chapters 56
Start page 29
End page 38
Total pages 10
Publisher Springer Berlin Heidelberg
Place of Publication Berlin, Germany
Keyword(s) model
frequent patterns
data mining
efficient
Summary Discovering frequent patterns plays an essential role in many data mining applications. The aim of frequent patterns is to obtain the information about the most common patterns that appeared together. However, designing an efficient model to mine these patterns is still demanding due to the capacity of current database size. Therefore, we propose an Efficient Frequent Pattern Mining Model (EFP-M2) to mine the frequent patterns in timely manner. The result shows that the algorithm in EFP-M2l is outperformed at least at 2 orders of magnitudes against the benchmarked FP-Growth.
ISBN 9783642347061
ISSN 0302-9743
Language eng
Field of Research 080501 Distributed and Grid Systems
080109 Pattern Recognition and Data Mining
Socio Economic Objective 890205 Information Processing Services (incl. Data Entry and Capture)
HERDC Research category B1 Book chapter
Copyright notice ©2012, Springer
Persistent URL http://hdl.handle.net/10536/DRO/DU:30051402

Document type: Book Chapter
Collection: School of Information Technology
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