Data Mining and Knowledge Discovery, Volume 2

Volume 2, Number 1, January 1998

Usama M. Fayyad:
Editorial. 5-7
Mauricio A. Hernández, Salvatore J. Stolfo:
Real-world Data is Dirty: Data Cleansing and The Merge/Purge Problem. 9-37
Craig Silverstein, Sergey Brin, Rajeev Motwani:
Beyond Market Baskets: Generalizing Association Rules to Dependence Rules. 39-68
Chun-Nan Hsu, Craig A. Knoblock:
Discovering Robust Knowledge from Databases that Change. 69-95
Kanti Bansal, Sanjeev Vadhavkar, Amar Gupta:
Brief Application Description. Neural Networks Based Forecasting Techniques for Inventory Control Applications. 97-102

Usama M. Fayyad:
Editorial. 115-119
Christopher J. C. Burges:
A Tutorial on Support Vector Machines for Pattern Recognition. 121-167
Jörg Sander, Martin Ester, Hans-Peter Kriegel, Xiaowei Xu:
Density-Based Clustering in Spatial Databases: The Algorithm GDBSCAN and Its Applications. 169-194
Rosa Meo, Giuseppe Psaila, Stefano Ceri:
An Extension to SQL for Mining Association Rules. 195-224

Raymond T. Ng, Jiawei Han, Laks V. S. Lakshmanan:
Editorial. 231-232
Sau Dan Lee, David Wai-Lok Cheung, Ben Kao:
Is Sampling Useful in Data Mining? A Case in the Maintenance of Discovered Association Rules. 233-262
Jef Wijsen, Robert Meersman:
On the Complexity of Mining Quantitative Association Rules. 263-281
Zhexue Huang:
Extensions to the k-Means Algorithm for Clustering Large Data Sets with Categorical Values. 283-304

Jon M. Kleinberg, Christos H. Papadimitriou, Prabhakar Raghavan:
A Microeconomic View of Data Mining. 311-324
Daniel Boley:
Principal Direction Divisive Partitioning. 325-344
Sreerama K. Murthy:
Automatic Construction of Decision Trees from Data: A Multi-Disciplinary Survey. 345-389
Yukinobu Hamuro, Naoki Katoh, Yasuyuki Matsuda, Katsutoshi Yada:
Mining Pharmacy Data Helps to Make Profits. 391-398

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