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Home > Research and Development in Knowledge Discovery and Data Mining: Second Pacific-Asia Conference, PAKDD' 98, Melbourne, Australia, April 15-17, 1998, Proceedings > Identifying relevant databases for multidatabase mining
Research and Development in Knowledge Discovery and Data Mining: Second Pacific-Asia Conference, PAKDD' 98, Melbourne, Australia, April 15-17, 1998, Proceedings |
Xindong Wu; Ramamohanarao Kotagiri; Kevin B. Korb
Springer Berlin Heidelberg
Research and Development in Knowledge Discovery and Data Mining: Second Pacific-Asia Conference, PAKDD' 98, Melbourne, Australia, April 15-17, 1998, Proceedings
Identifying relevant databases for multidatabase mining
Authors

Huan Liu; Hongjun Lu; Jun Yao

ARI Id

1664706890032_2831665

Access

Not Available Free

Pages

210-221

DOI

10.1007/3-540-64383-4_18

Chapter URL

https://rd.springer.com/chapter/10.1007/3-540-64383-4_18

Table of Contents of Book
Showing 1 to 20 of 53 entries
Chapters/HeadingsAuthor(s)PagesInfo
Front Matter
Knowledge acquisition for goal prediction in a multi-user adventure game
D. W. Albrecht; A. E. Nicholson; I. Zukerman
1-12
Hybrid data mining systems: The next generation
Sarabjot S. Anand; John G. Hughes
13-24
Discovering case knowledge using data mining
S. S. Anand; D. Patterson; J. G. Hughes; D. A. Bell
25-35
Discovery of association rules over ordinal data: A new and faster algorithm and its application to basket analysis
Oliver Büchter; Rüdiger Wirth
36-47
Effect of data skewness in parallel mining of association rules
David W. Cheung; Yongqiao Xiao
48-60
Trend directed learning: A case study
Honghua Dai
61-71
Interestingness of discovered association rules in terms of neighborhood-based unexpectedness
Guozhu Dong; Jinyan Li
72-86
Point estimation using the Kullback-Leibler loss function and MML
David L. Dowe; Rohan A. Baxter; Jonathan J. Oliver; Chris S. Wallace
87-95
Single factor analysis in MML mixture modelling
Russell T. Edwards; David L. Dowe
96-109
Discovering associations in spatial data — An efficient medoid based approach
Vladimir Estivill-Castrol; Alan T. Murray
110-121
Data mining using dynamically constructed recurrent fuzzy neural networks
Yakov Frayman; Lipo Wang
122-131
CCAIIA: Clustering categorical attributes into interesting association rules
Brett Gray; M. E. Orlowska
132-143
Selective materialization: An efficient method for spatial data cube construction
Jiawei Han; Nebojsa Stefanovic; Krzysztof Koperski
144-158
Mining market basket data using share measures and characterized itemsets
Robert J. Hilderman; Colin L. Carter; Howard J. Hamilton; Nick Cercone
159-173
Automatic visualization method for visual data mining
Yuichi Iizuka; Hisako Shiohara; Tetsuya Iizuka; Seiji Isobe
174-185
Rough-set inspired approach to knowledge discovery in business databases
W. Kowalczyk; Z. Piasta
186-197
Representative association rules
Marzena Kryszkiewicz
198-209
Identifying relevant databases for multidatabase mining
Huan Liu; Hongjun Lu; Jun Yao
210-221
Minimum message length segmentation
Jonathan J. Oliver; Rohan A. Baxter; Chris S. Wallace
222-233
Chapters/HeadingsAuthor(s)PagesInfo
Showing 1 to 20 of 53 entries
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