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OverviewRecent 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. Full Product DetailsAuthor: Gordon M RedwinePublisher: Gordon M. Redwine Imprint: Gordon M. Redwine Dimensions: Width: 15.20cm , Height: 0.90cm , Length: 22.90cm Weight: 0.231kg ISBN: 9783427330684ISBN 10: 3427330680 Pages: 168 Publication Date: 02 May 2023 Audience: General/trade , General Format: Paperback Publisher's Status: Active Availability: In stock  We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately. Table of ContentsReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
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