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

Volume 2, Number 2, June 1998

• 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

Volume 2, Number 3, September 1998

• 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

Volume 2, Number 4, December 1998

• 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