Tree-based Algorithms for Incremental, Utility, and Fuzzy Data Mining

Jerry Chun-Wei Lin

ISBN 10: 3659677221 / ISBN 13: 9783659677229

Verlag: LAP LAMBERT Academic Publishing Mär 2015, 2015

Beschreibung

This item is printed on demand - Print on Demand Titel. Neuware -In the first part of this book, three Pre-FUFP maintenance algorithms are thus proposed to efficiently maintain and update the FUFP-tree structures regardless of whether records are inserted, deleted or modified in dynamic databases. In the second part of this book, a novel HUP-tree algorithm is proposed to efficiently mine the high utility itemsets based on the downward closure property. A HUP tree is first designed to keep the related information for later mining process. A HUP-growth mining algorithm is then presented to efficiently mine high utility itemsets from it. In the third part of this book, we attempt to extend the FP-tree algorithm for handling quantitative data from the global values of fuzzy regions. Thus, the fuzzy FP-tree algorithm, the compressed fuzzy frequent pattern tree (CFFP-tree) algorithm, and the upper-bound fuzzy frequent pattern tree (UBFFP-tree) algorithm are then proposed to efficiently mine the fuzzy frequent itemsets.Books on Demand GmbH, Überseering 33, 22297 Hamburg 172 pp. Englisch. Bestandsnummer des Verkäufers 9783659677229

Bibliografische Details

Titel: Tree-based Algorithms for Incremental, ...

Verlag: LAP LAMBERT Academic Publishing Mär 2015

Erscheinungsdatum: 2015

Einband: Taschenbuch

Zustand: Neu

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Inhaltsangabe:

In the first part of this book, three Pre-FUFP maintenance algorithms are thus proposed to efficiently maintain and update the FUFP-tree structures regardless of whether records are inserted, deleted or modified in dynamic databases. In the second part of this book, a novel HUP-tree algorithm is proposed to efficiently mine the high utility itemsets based on the downward closure property. A HUP tree is first designed to keep the related information for later mining process. A HUP-growth mining algorithm is then presented to efficiently mine high utility itemsets from it. In the third part of this book, we attempt to extend the FP-tree algorithm for handling quantitative data from the global values of fuzzy regions. Thus, the fuzzy FP-tree algorithm, the compressed fuzzy frequent pattern tree (CFFP-tree) algorithm, and the upper-bound fuzzy frequent pattern tree (UBFFP-tree) algorithm are then proposed to efficiently mine the fuzzy frequent itemsets.