Rare Association Rule Mining And Knowledge Discovery
by Yun Sing Koh
The growing complexity and volume of modern databases make it increasingly important for researchers and practitioners involved with association rule mining to make sense of the information they contain. Rare Association Rule Mining and Knowledge Discovery: Technologies for Infrequent and Critical Event Detection provides readers with an in-depth compendium of
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The growing complexity and volume of modern databases make it increasingly important for researchers and practitioners involved with association rule mining to make sense of the information they contain. Rare Association Rule Mining and Knowledge Discovery: Technologies for Infrequent and Critical Event Detection provides readers with an in-depth compendium of current issues, trends, and technologies in association rule mining. Covering a comprehensive range of topics, this book discusses underlying frameworks, mining techniques, interest metrics, and real-world application domains within the field.
Product Details
- ISBN-13:
- 9781605667546
- Publisher:
- IGI Global
- Publication date:
- 12/23/2010
- Series:
- Advances in Data Warehousing and Mining (ADWM) Book Series
- Pages:
- 320
- Product dimensions:
- 8.70(w) x 11.20(h) x 1.10(d)
Table of Contents
Ch. 1 Rare Association Rule Mining: An Overview 1
Ch. 2 Association Rule and Quantitative Association Rule Mining among Infrequent Items 15
Ch. 3 Replacing Support in Association Rule Mining 33
Ch. 4 Effective Mining of Weighted Fuzzy Association Rules 47
Ch. 5 Rare Class Association Rule Mining with Multiple Imbalanced Attributes 66
Ch. 6 A Multi-Methodological Approach to Rare Association Rule Mining 76
Ch. 7 Finding Minimal Infrequent Elements in Multi-Dimensional Data Defined over Partially Ordered Sets and its Applications 98
Ch. 8 Discovering Interesting Patterns in Numerical Data with Background Knowledge 118
Ch. 9 Mining Rare Association Rules by Discovering Quasi-Functional Dependencies: An Incremental Approach 131
Ch. 10 Mining Unexpected Sequential Patterns and Implication Rules 150
Ch. 11 Mining Hidden Association Rules from Real-Life Data 168
Ch. 12 Strong Symmetric Association Rules and Interestingness Measures 185
Ch. 13 He Wasn't There Again Today 205
Ch. 14 Filtering Association Rules by Their Semantics and Structures 216
Ch. 15 Creating Risk-Scores in Very Imbalanced Datasets: Predicting Extremely Violent Crime among Criminal Offenders Following Release from Prison 231
Ch. 16 Boosting Prediction Accuracy of Bad Payments in Financial Credit Applications 255
Compilation of References 270
Index 296
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