Ebook: Data Mining: Special Issue in Annals of Information Systems

Over the course of the last twenty years, research in data mining has seen a substantial increase in interest, attracting original contributions from various disciplines including computer science, statistics, operations research, and information systems. Data mining supports a wide range of applications, from medical decision making, bioinformatics, web-usage mining, and text and image recognition to prominent business applications in corporate planning, direct marketing, and credit scoring. Research in information systems equally reflects this inter- and multidisciplinary approach, thereby advocating a series of papers at the intersection of data mining and information systems research.

This special issue of Annals of Information Systems contains original papers and substantial extensions of selected papers from the 2007 and 2008 International Conference on Data Mining (DMIN’07 and DMIN’08, Las Vegas, NV) that have been rigorously peer-reviewed. The issue brings together topics on both information systems and data mining, and aims to give the reader a current snapshot of the contemporary research and state of the art practice in data mining.

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Over the course of the last twenty years, research in data mining has seen a substantial increase in interest, attracting original contributions from various disciplines including computer science, statistics, operations research, and information systems. Data mining supports a wide range of applications, from medical decision making, bioinformatics, web-usage mining, and text and image recognition to prominent business applications in corporate planning, direct marketing, and credit scoring. Research in information systems equally reflects this inter- and multidisciplinary approach, thereby advocating a series of papers at the intersection of data mining and information systems research.

This special issue of Annals of Information Systems contains original papers and substantial extensions of selected papers from the 2007 and 2008 International Conference on Data Mining (DMIN’07 and DMIN’08, Las Vegas, NV) that have been rigorously peer-reviewed. The issue brings together topics on both information systems and data mining, and aims to give the reader a current snapshot of the contemporary research and state of the art practice in data mining.

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Over the course of the last twenty years, research in data mining has seen a substantial increase in interest, attracting original contributions from various disciplines including computer science, statistics, operations research, and information systems. Data mining supports a wide range of applications, from medical decision making, bioinformatics, web-usage mining, and text and image recognition to prominent business applications in corporate planning, direct marketing, and credit scoring. Research in information systems equally reflects this inter- and multidisciplinary approach, thereby advocating a series of papers at the intersection of data mining and information systems research.

This special issue of Annals of Information Systems contains original papers and substantial extensions of selected papers from the 2007 and 2008 International Conference on Data Mining (DMIN’07 and DMIN’08, Las Vegas, NV) that have been rigorously peer-reviewed. The issue brings together topics on both information systems and data mining, and aims to give the reader a current snapshot of the contemporary research and state of the art practice in data mining.

Content:
Front Matter....Pages i-xiii
Data Mining and Information Systems: Quo Vadis?....Pages 1-15
Front Matter....Pages 17-17
Response-Based Segmentation Using Finite Mixture Partial Least Squares....Pages 19-49
Front Matter....Pages 51-51
Building Acceptable Classification Models....Pages 53-74
Mining Interesting Rules Without Support Requirement: A General Universal Existential Upward Closure Property....Pages 75-98
Classification Techniques and Error Control in Logic Mining....Pages 99-119
Front Matter....Pages 121-121
An Extended Study of the Discriminant Random Forest....Pages 123-146
Prediction with the SVM Using Test Point Margins....Pages 147-158
Effects of Oversampling Versus Cost-Sensitive Learning for Bayesian and SVM Classifiers....Pages 159-192
The Impact of Small Disjuncts on Classifier Learning....Pages 193-226
Front Matter....Pages 227-227
Predicting Customer Loyalty Labels in a Large Retail Database: A Case Study in Chile....Pages 229-253
PCA-based Time Series Similarity Search....Pages 255-276
Evolutionary Optimization of Least-Squares Support Vector Machines....Pages 277-297
Genetically Evolved kNN Ensembles....Pages 299-313
Front Matter....Pages 315-315
Behaviorally Founded Recommendation Algorithm for Browsing Assistance Systems....Pages 317-334
Using Web Text Mining to Predict Future Events: A Test of the Wisdom of Crowds Hypothesis....Pages 335-350
Front Matter....Pages 351-351
Avoiding Attribute Disclosure with the (Extended) p-Sensitive k-Anonymity Model....Pages 353-373
Privacy-Preserving Random Kernel Classification of Checkerboard Partitioned Data....Pages 375-387

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Over the course of the last twenty years, research in data mining has seen a substantial increase in interest, attracting original contributions from various disciplines including computer science, statistics, operations research, and information systems. Data mining supports a wide range of applications, from medical decision making, bioinformatics, web-usage mining, and text and image recognition to prominent business applications in corporate planning, direct marketing, and credit scoring. Research in information systems equally reflects this inter- and multidisciplinary approach, thereby advocating a series of papers at the intersection of data mining and information systems research.

This special issue of Annals of Information Systems contains original papers and substantial extensions of selected papers from the 2007 and 2008 International Conference on Data Mining (DMIN’07 and DMIN’08, Las Vegas, NV) that have been rigorously peer-reviewed. The issue brings together topics on both information systems and data mining, and aims to give the reader a current snapshot of the contemporary research and state of the art practice in data mining.

Content:
Front Matter....Pages i-xiii
Data Mining and Information Systems: Quo Vadis?....Pages 1-15
Front Matter....Pages 17-17
Response-Based Segmentation Using Finite Mixture Partial Least Squares....Pages 19-49
Front Matter....Pages 51-51
Building Acceptable Classification Models....Pages 53-74
Mining Interesting Rules Without Support Requirement: A General Universal Existential Upward Closure Property....Pages 75-98
Classification Techniques and Error Control in Logic Mining....Pages 99-119
Front Matter....Pages 121-121
An Extended Study of the Discriminant Random Forest....Pages 123-146
Prediction with the SVM Using Test Point Margins....Pages 147-158
Effects of Oversampling Versus Cost-Sensitive Learning for Bayesian and SVM Classifiers....Pages 159-192
The Impact of Small Disjuncts on Classifier Learning....Pages 193-226
Front Matter....Pages 227-227
Predicting Customer Loyalty Labels in a Large Retail Database: A Case Study in Chile....Pages 229-253
PCA-based Time Series Similarity Search....Pages 255-276
Evolutionary Optimization of Least-Squares Support Vector Machines....Pages 277-297
Genetically Evolved kNN Ensembles....Pages 299-313
Front Matter....Pages 315-315
Behaviorally Founded Recommendation Algorithm for Browsing Assistance Systems....Pages 317-334
Using Web Text Mining to Predict Future Events: A Test of the Wisdom of Crowds Hypothesis....Pages 335-350
Front Matter....Pages 351-351
Avoiding Attribute Disclosure with the (Extended) p-Sensitive k-Anonymity Model....Pages 353-373
Privacy-Preserving Random Kernel Classification of Checkerboard Partitioned Data....Pages 375-387
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