Post-mining of association rules: techniques for effective knowledge extraction
"This book provides a systematic collection on the post-mining, summarization and presentation of association rule, as well as new forms of association rules"--Provided by publisher
Saved in:
| Format: | Book |
|---|---|
| Language: | English |
| Published: |
Hershey, Pa. [u.a.]
Information Science Reference
2009
|
| Series: | Premier reference source
|
| Subjects: | |
| Online Access: | Inhaltsverzeichnis |
| Summary: | "This book provides a systematic collection on the post-mining, summarization and presentation of association rule, as well as new forms of association rules"--Provided by publisher |
| Item Description: | Literaturangaben |
| Physical Description: | XXI, 372 S. Ill., graph. Darst. |
| ISBN: | 9781605664040 |
Staff View
MARC
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Record in the Search Index
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|---|---|
| adam_text | Table
of
Contents
Foreword
.............................................................................................................................................xiv
Preface
.................................................................................................................................................xvi
Acknowledgement
..............................................................................................................................xxi
Section I
Introduction
Chapter I
Association Rules: An Overview
...........................................................
Paul D. McNicholas, University ofGuelph, Ontario, Canada
Yanchang Zhao, University of Technology, Sydney, Australia
Section II
Identifying Interesting Rules
Chapter II
From Change Mining to Relevance Feedback: A Unified View on
Assessing Rule Interestingness
.............................................................................................................12
Mirko Boettcher,
University of Magdeburg, Germany
Georg Ruß,
University of Magdeburg, Germany
Detlef
Nauck,
ВТ
Group pic, UK
Rudolf
Kruse,
University of Magdeburg, Germany
Chapter III
Combining Data-Driven and User-Driven Evaluation Measures to Identify Interesting Rules
...........38
Solange
Oliveira Rezende,
University of
São
Paulo, Brazil
Edson Augusto
Melanda, Federal University of
São
Carlos, Brazil
Magaly
Lika Fujimoto,
University of
São
Paulo, Brazil
Roberta Akemi Sinoara, University of
São
Paulo, Brazil
Veronica
Oliveira de Carvalho,
University of
Oeste Paulista,
Brazil
Chapter IV
Semantics-Based Classification of Rule Interestingness Measures
......................................................56
Julien Blanchard,
Polytechnic School of Nantes University, France
Fabrice Guillet,
Polytechnic School of Nantes University, France
Pascale Kuntz,
Polytechnic School of Nantes University, France
Section III
Post-Analysis and Post-Mining of Association Rules
Chapter V
Post-Processing for Rule Reduction Using Closed Set
.........................................................................81
Huawen Liu, Jilin University, PR. China
Jigui Sun, Jilin University, PR. China
Huijie Zhang, Northeast Normal University, PR. China
Chapter VI
A Conformity Measure Using Background Knowledge for Association Rules:
Application to Text Mining
.................................................................................................................100
Hacène
Cherfi, INRIA Sophia
Antipolis,
France
Amedeo Napoli,
LORIA
—
INRIA, France
Yannick Toussaint,
LORIA
—
INRIA, France
Chapter
VII
Continuous Post-Mining of Association Rules in a Data Stream Management System
.....................116
Hetal Thakkar, University of California, Los Angeles, USA
Barzan Mozafari, University of California, Los Angeles, USA
Carlo Zaniolo, University of California, Los Angeles, USA
Chapter
VIII
QROC: A Variation of ROC Space to Analyze Item Set Costs/Benefits in Association Rules
...........133
Ronaldo
Cristiano Prati,
UFABC
Universidade Federal
do ABC, Brazil
Section IV
Rule Selection for Classification
Chapter IX
Variations on Associative Classifiers and Classification Results Analyses
........................................150
Mar ia-Luiza
Antonie,
University of Alberta, Canada
David Chodos, University of Alberta, Canada
Osmar
Zaïane,
University of Alberta, Canada
Chapter X
Selection of High Quality Rules in Associative Classification
...........................................................173
Silvia Chiusano,
Politécnico
di
Torino, Italy
Paolo
Garza, Politecnico di
Torino, Italy
Section V
Visualization and Representation of Association Rules
Chapter XI
Meta-Knowledge Based Approach for an Interactive Visualization of Large
Amounts of Association Rules
............................................................................................................200
Sadok Ben Yahia, Faculty of Sciences of Tunis, Tunisia
Olivier Couturier, Centre
de
Recherche
en Informatique de
Lens
(CRÌI),
France
Tarek
Hamrouni, Faculty of Sciences of Tunis, Tunisia
Engelbert
Mephu Nguifo, Centre
de
Recherche
en Informatique de
Lens (CRIL), France
Chapter
XII
Visualization to Assist the Generation and Exploration of Association Rules
...................................224
Claudio Haruo
Yamamoto,
Universidade de São
Paulo, Brazil
Maria
Cristina Ferreira de Oliveira, Universidade de São Paulo,
Brazil
Solange
Oliveira Rezende, Universidade de São Paulo,
Brazil
Chapter
XIII
Frequent Closed ltemsets Based Condensed Representations for Association Rules
........................246
Nicolas Pasquier, University of Nice Sophia-
Antipolis,
France
Section VI
Maintenance of Association Rules and New Forms of Association Rules
Chapter
XIV
Maintenance of Frequent Patterns: A Survey
......................................................................................273
Mengling Feng, Nanyang Technological University, Singapore
&
National University of
Singapore, Singapore
Jinyan Li, Nanyang Technological University, Singapore
Guozhu Dong, Wright State University, USA
Limsoon Wong, National University of Singapore, Singapore
Chapter XV
Mining Conditional Contrast Patterns
................................................................................................294
Guozhu Dong, Wright State University, USA
Jinyan Li, Nanyang Technological University, Singapore
Guimei Liu, National University of Singapore, Singapore
Limsoon Wong, National University of Singapore, Singapore
Chapter
XVI
Multidimensional Model-Based Decision Rules Mining
...................................................................311
Qinrong Feng, Tongji University, China
Duoqian
Miao,
Tongji University, China
Ruizhi Wang, Tongji University, China
Compilation of References
...............................................................................................................335
About the Contributors
....................................................................................................................361
Index
...................................................................................................................................................370
|
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| spelling | Post-mining of association rules techniques for effective knowledge extraction Yanchang Zhao ; Chengqi Zhang ; Longbing Cao [eds.] Hershey, Pa. [u.a.] Information Science Reference 2009 XXI, 372 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Premier reference source Literaturangaben "This book provides a systematic collection on the post-mining, summarization and presentation of association rule, as well as new forms of association rules"--Provided by publisher Paired-association learning Association of ideas Data mining Wissensextraktion (DE-588)4546354-2 gnd rswk-swf (DE-588)4143413-4 Aufsatzsammlung gnd-content Wissensextraktion (DE-588)4546354-2 s DE-604 Zhao, Yanchang Sonstige oth Zhang, Chengqi Sonstige oth Cao, Longbing Sonstige (DE-588)1052331815 oth Erscheint auch als Online-Ausgabe 978-1-60566-405-7 Digitalisierung UB Bamberg application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017734365&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Post-mining of association rules techniques for effective knowledge extraction Paired-association learning Association of ideas Data mining Wissensextraktion (DE-588)4546354-2 gnd |
| subject_GND | (DE-588)4546354-2 (DE-588)4143413-4 |
| title | Post-mining of association rules techniques for effective knowledge extraction |
| title_auth | Post-mining of association rules techniques for effective knowledge extraction |
| title_exact_search | Post-mining of association rules techniques for effective knowledge extraction |
| title_full | Post-mining of association rules techniques for effective knowledge extraction Yanchang Zhao ; Chengqi Zhang ; Longbing Cao [eds.] |
| title_fullStr | Post-mining of association rules techniques for effective knowledge extraction Yanchang Zhao ; Chengqi Zhang ; Longbing Cao [eds.] |
| title_full_unstemmed | Post-mining of association rules techniques for effective knowledge extraction Yanchang Zhao ; Chengqi Zhang ; Longbing Cao [eds.] |
| title_short | Post-mining of association rules |
| title_sort | post mining of association rules techniques for effective knowledge extraction |
| title_sub | techniques for effective knowledge extraction |
| topic | Paired-association learning Association of ideas Data mining Wissensextraktion (DE-588)4546354-2 gnd |
| topic_facet | Paired-association learning Association of ideas Data mining Wissensextraktion Aufsatzsammlung |
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