Research and Development in Knowledge Discovery and Data Mining: Second Pacific-Asia Conference, PAKDD'98, Melbourne, Australia, April 15-17, 1998, ProceedingsXindong Wu, Ramamohanarao Kotagiri, Kevin B. Korb Springer, 2005 M09 16 - 434 pages This book constitutes the refereed proceedings of the Second Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD-98, held in Melbourne, Australia, in April 1998. The book presents 30 revised full papers selected from a total of 110 submissions; also included are 20 poster presentations. The papers contribute new results to all current aspects in knowledge discovery and data mining on the research level as well as on the level of systems development. Among the areas covered are machine learning, information systems, the Internet, statistics, knowledge acquisition, data visualization, software reengineering, and knowledge based systems. |
Contents
| 1 | |
The Next Generation | 13 |
3 Discovering Case Knowledge Using Data Mining | 25 |
A New and Faster Algorithm and Its Application to Basket Analysis | 36 |
5 Effect of Data Skewness in Parallel Mining of Association Rules | 48 |
A Case Study | 61 |
7 Interestingness of Discovered Association Rules in Terms of NeighborhoodBased Unexpectedness | 72 |
8 Point Estimation Using the KullbackLeibler Loss Function and MML | 87 |
29 Scaling Up the Rule Generation of C45 | 348 |
30 Data Mining Based on the Generalization DistributionTable and Rough Sets | 360 |
31 Constructing Personalized Information Agents | 374 |
32 Towards Real Time Discovery from Distributed Information Sources | 376 |
33 Constructing Conceptual Scales in Formal Concept Analysis | 378 |
34 The Hunter and the Hunted Modelling the Relationship Between Web Pages and Search Engines | 380 |
35 An Efficient Global Discretization Method | 383 |
36 Learning User Preferences on the WEB | 385 |
9 Single Factor Analysis in MML Mixture Modelling | 96 |
10 Discovering Associations in Spatial Data An Efficient Medoid Based Approach | 110 |
11 Data Mining Using Dynamically Constructed Recurrent Fuzzy Neural Networks | 122 |
Clustering Categorical Attributes into Interesting Association Rules | 132 |
An Efficient Method for Spatial Data Cube Construction | 144 |
14 Mining Market Basket Data Using Share Measures and Characterized Itemsets | 159 |
15 Automatic Visualization Method for Visual Data Mining | 174 |
16 RoughSet Inspired Approach to Knowledge Discovery in Business Databases | 186 |
17 Representative Association Rules | 198 |
18 Identifying Relevant Databases for Multidatabase Mining | 210 |
19 Minimum Message Length Segmentation | 222 |
20 Bayesian Classification Trees with Overlapping Leaves Applied to CreditScoring | 234 |
21 Contextual Text Representation for Unsupervised Knowledge Discovery in Texts | 246 |
22 Treatment of Missing Valuesfor Association Rules | 258 |
23 Mining Regression Rules and Regression Trees | 271 |
Hash Based Approach | 283 |
25 Wavelet Transform in Similarity Paradigm | 295 |
26 Improved Rule Discovery Performance on Uncertainty | 310 |
27 Feature Mining and Mapping of Collinear Data | 322 |
28 Knowledge Discovery in Discretionary Legal Domains | 336 |
37 Using Rough Sets for Knowledge Discovery in the Development of a Decision Support System for Issuing Smog Alerts | 388 |
38 Empirical Results on Data Dimensionality Reduction Using the Divided SelfOrganizing Map | 390 |
39 Mining Association Rules with Linguistic Cloud Models | 392 |
40 A Data Mining Approach for Query Refinement | 394 |
A ConflictFree Multivariate Discretization Algorithm | 397 |
42 Characteristic Rule Induction Algorithm for Data Mining | 399 |
43 DataMining Massive Time Series Astronomical Data Sets A Case Study | 401 |
44 Multiple Databases Partial Reasoning and Knowledge Discovery | 403 |
45 Design Recovery with Data Mining Techniques | 405 |
46 The CLARET Algorithm | 407 |
A Hybrid Technique for Classifying Myocardial Infarction Data Containing Unknown Attribute Values | 409 |
48 Modelling Decision Tables from Data | 412 |
49 A Classification and Relationship Extraction Scheme for Relational Databases Based on Fuzzy Logic | 414 |
50 Mining Association Rules for Estimation and Prediction | 417 |
51 Rule Generalization by Condition Combination | 420 |
Author Index | 423 |
Lecture Notes in Artificial Intelligence LNAI | 425 |
Lecture Notes in Computer Science | 426 |
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Research and Development in Knowledge Discovery and Data Mining Xindong Wu,Ramamohanarao Kotagiri,Kevin B. Korb No preview available - 2014 |
Common terms and phrases
accuracy actions algorithm analysis applied approach Artificial Intelligence association rules attribute values average C.S. Wallace candidate sequences categorical categorical variables classification clustering collocational expressions Computer Science concept contains cuboid customer-sequence data cube data mining data set data skewness data warehouse decision tree defined definition denoted discovered distribution domain evaluation example extracted factor frequent itemsets function global share induction input interestingness itemset k-itemsets k-NN Knowledge Discovery large databases Machine Learning mainModel measure message length method Minimum Message Length minimum support mining association rules missing values mixture modelling MML estimator neural networks nodes number of rules OLAP parameters partition patterns performance Piatetsky-Shapiro prediction problem Proc query quest Quinlan raw trees regression rules relevant representative association rules Rough Sets ruleset Section segmentation selection statistical subset support counts Table techniques total item count training set transaction tuples variable wavelet Y₁