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Interesting patterns for clustering high-dimensional data

Gordon M Redwine

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English
Gordon M. Redwine
02 May 2023
Recent advances in data mining allow for exploiting patterns as the primary means for clustering and classifying large collections of data. In this thesis, we present three advances in pattern-based clustering technology, an advance in semi-supervised pattern-based classification, and a related advance in pattern frequency counting. In our first contribution, we analyze numerous deficiencies with traditional patternsignificance measures such as support and confidence, and propose a web image clustering algorithm that uses an objective interestingness measure to identify significant patterns, yielding measurably better clustering quality.

By:  
Imprint:   Gordon M. Redwine
Dimensions:   Height: 229mm,  Width: 152mm,  Spine: 9mm
Weight:   231g
ISBN:   9783427330684
ISBN 10:   3427330680
Pages:   168
Publication Date:  
Audience:   General/trade ,  ELT Advanced
Format:   Paperback
Publisher's Status:   Active

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