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CoCluster: Efficient Mining Maximal Trend Biclusters Without Candidate Maintenance in Discrete Resource Effectiveness Matrix Read chapter Read first chapter

2014 | OriginalPaper | Chapter

5. Efficient Mining Maximal Trend Biclusters in Real-Valued Resource Effectiveness Matrix: The CeCluster Algorithm

Authors : Lihua Zhang, Miao Wang, Qingfan Gu, Zhengjun Zhai, Guoqing Wang

Published in: Proceedings of the First Symposium on Aviation Maintenance and Management-Volume II

Publisher: Springer Berlin Heidelberg

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Abstract

The efficiency of resources is the footstone for building prognostics and health management system or safety system. In this study, we proposed an efficient bicluster mining algorithm: CeCluster algorithm, which mines trend bicluster in real-valued resource effectiveness matrices. To improve the mining efficiency, CeCluster algorithm mines maximal trend bicluster using the method of column extension and multiple pruning strategies without candidate maintenance. CeCluster algorithm can not only mine resource patterns with effectiveness in the downtrend, but also mine those with effectiveness in the uptrend. CeCluster algorithm can also mine resource patterns without change of effectiveness. The experimental result shows our algorithm is efficient than traditional algorithm.

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previous chapter Efficient Mining Frequent Closed Resource Patterns in Resource Effectiveness Data: The MFPattern Approach
next chapter Research About Algorithm and Application of Tunable Activation Function Neural Network
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Metadata
Title
Efficient Mining Maximal Trend Biclusters in Real-Valued Resource Effectiveness Matrix: The CeCluster Algorithm
Authors
Lihua Zhang
Miao Wang
Qingfan Gu
Zhengjun Zhai
Guoqing Wang
Copyright Year
2014
Publisher
Springer Berlin Heidelberg
Book
Proceedings of the First Symposium on Aviation Maintenance and Management-Volume II

Print ISBN: 978-3-642-54232-9

Electronic ISBN: 978-3-642-54233-6

Copyright Year: 2014

DOI
https://doi.org/10.1007/978-3-642-54233-6_5