5. KDD 1999: San Diego, CA, USA

• Rakesh Agrawal:
  Data Mining: Crossing the Chasm (Invited talk, Abstract only). 2
  
• Richard D. Hackathorn:
  Farming the Web for Systematic Business Intelligence (Invited talk, Abstract only). 3
  
• Daryl Pregibon:
  2001: A Statistical Odyssey (Invited talk, Abstract only). 4
  
• William DuMouchel, Chris Volinsky, Theodore Johnson, Corinna Cortes, Daryl Pregibon:
  Squashing Flat Files Flatter. 6-15
  
• Bjornar Larsen, Chinatsu Aone:
  Fast and Effective Text Mining Using Linear-Time Document Clustering. 16-22
  
• Foster J. Provost, David Jensen, Tim Oates:
  Efficient Progressive Sampling. 23-32
  
• Valery Guralnik, Jaideep Srivastava:
  Event Detection from Time Series Data. 33-42
  
• Guozhu Dong, Jinyan Li:
  Efficient Mining of Emerging Patterns: Discovering Trends and Differences. 43-52
  
• Tom Fawcett, Foster J. Provost:
  Activity Monitoring: Noticing Interesting Changes in Behavior. 53-62
  
• Scott Gaffney, Padhraic Smyth:
  Trajectory Clustering with Mixtures of Regression Models. 63-72
  
• Venkatesh Ganti, Johannes Gehrke, Raghu Ramakrishnan:
  CACTUS - Clustering Categorical Data Using Summaries. 73-83
  
• Chun Hung Cheng, Ada Wai-Chee Fu, Yi Zhang:
  Entropy-based Subspace Clustering for Mining Numerical Data. 84-93
  
• D. R. Mani, James Drew, Andrew Betz, Piew Datta:
  Statistics and Data Mining Techniques for Lifetime Value Modeling. 94-103
  
• Seth Rogers, Pat Langley, Christopher Wilson:
  Mining GPS Data to Augment Road Models. 104-113
  
• Wenke Lee, Salvatore J. Stolfo, Kui W. Mok:
  Mining in a Data-Flow Environment: Experience in Network Intrusion Detection. 114-124
  
• Bing Liu, Wynne Hsu, Yiming Ma:
  Pruning and Summarizing the Discovered Associations. 125-134
  
• Sergey Brin, Rajeev Rastogi, Kyuseok Shim:
  Mining Optimized Gain Rules for Numeric Attributes. 135-144
  
• Roberto J. Bayardo Jr., Rakesh Agrawal:
  Mining the Most Interesting Rules. 145-154
  
• Pedro Domingos:
  MetaCost: A General Method for Making Classifiers Cost-Sensitive. 155-164
  
• Dimitris Meretakis, Beat Wüthrich:
  Extending Naïve Bayes Classifiers Using Long Itemsets. 165-174
  
• Francesco Bonchi, Fosca Giannotti, Gianni Mainetto, Dino Pedreschi:
  A Classification-Based Methodology for Planning Audit Strategies in Fraud Detection. 175-184
  
• Gregory Piatetsky-Shapiro, Brij M. Masand:
  Estimating Campaign Benefits and Modeling Lift. 185-193
  
• William J. E. Potts:
  Generalized Additive Neural Networks. 194-200
  
• Charu C. Aggarwal, Joel L. Wolf, Kun-Lung Wu, Philip S. Yu:
  Horting Hatches an Egg: A New Graph-Theoretic Approach to Collaborative Filtering. 201-212
  
• Jef Wijsen, Raymond T. Ng, Toon Calders:
  Discovering Roll-Up Dependencies. 213-222
  
• Jayavel Shanmugasundaram, Usama M. Fayyad, Paul S. Bradley:
  Compressed Data Cubes for OLAP Aggregate Query Approximation on Continuous Dimensions. 223-232
  
• Kristin P. Bennett, Usama M. Fayyad, Dan Geiger:
  Density-Based Indexing for Approximate Nearest-Neighbor Queries. 233-243
  
• Biswadeep Nag, Prasad Deshpande, David J. DeWitt:
  Using a Knowledge Cache for Interactive Discovery of Association Rules. 244-253
  
• Tom Brijs, Gilbert Swinnen, Koen Vanhoof, Geert Wets:
  Using Association Rules for Product Assortment Decisions: A Case Study. 254-260
  
• Yonatan Aumann, Yehuda Lindell:
  A Statistical Theory for Quantitative Association Rules. 261-270
  
• Nadeem Ahmed Syed, Huan Liu, Kah Kay Sung:
  A Study of Support Vectors on Model Independent Example Selection. 272-276
  
• Dan Pelleg, Andrew W. Moore:
  Accelerating Exact k-means Algorithms with Geometric Reasoning. 277-281
  
• Yun-Wu Huang, Philip S. Yu:
  Adaptive Query Processing for Time-Series Data. 282-286
  
• Necip Fazil Ayan, Abdullah Uz Tansel, M. Erol Arkun:
  An Efficient Algorithm to Update Large Itemsets with Early Pruning. 287-291
  
• Jesús Cerquides:
  Applying General Bayesian Techniques to Improve TAN Induction. 292-296
  
• Anthony K. H. Tung, Hongjun Lu, Jiawei Han, Ling Feng:
  Breaking the Barrier of Transactions: Mining Inter-Transaction Association Rules. 297-301
  
• Stephen D. Bay, Michael J. Pazzani:
  Detecting Change in Categorical Data: Mining Contrast Sets. 302-306
  
• Jason Tsong-Li Wang, Xiong Wang, King-Ip Lin, Dennis Shasha, Bruce A. Shapiro, Kaizhong Zhang:
  Evaluating a Class of Distance-Mapping Algorithms for Data Mining and Clustering. 307-311
  
• Tian Zhang, Raghu Ramakrishnan, Miron Livny:
  Fast Density Estimation Using CF-Kernel for Very Large Databases. 312-316
  
• Nadeem Ahmed Syed, Huan Liu, Kah Kay Sung:
  Handling Concept Drifts in Incremental Learning with Support Vector Machines. 317-321
  
• Tim Oates:
  Identifying Distinctive Subsequences in Multivariate Time Series by Clustering. 322-326
  
• Corinna Cortes, Daryl Pregibon:
  Information Mining Platforms: An Infrastructure for KDD Rapid Deployment. 327-331
  
• Sigal Sahar:
  Interestingness via What is Not Interesting. 332-336
  
• Bing Liu, Wynne Hsu, Yiming Ma:
  Mining Association Rules with Multiple Minimum Supports. 337-341
  
• Neal Lesh, Mohammed Javeed Zaki, Mitsunori Ogihara:
  Mining Features for Sequence Classification. 342-346
  
• Vasileios Megalooikonomou, Christos Davatzikos, Edward Herskovits:
  Mining Lesion-Deficit Associations in a Brain Image Database. 347-351
  
• Charu C. Aggarwal, Stephen C. Gates, Philip S. Yu:
  On the Merits of Building Categorization Systems by Supervised Clustering. 352-356
  
• Heikki Mannila, Dmitry Pavlov, Padhraic Smyth:
  Prediction with Local Patterns using Cross-Entropy. 357-361
  
• Wei Fan, Salvatore J. Stolfo, Junxin Zhang:
  The Application of AdaBoost for Distributed, Scalable and On-Line Learning. 362-366
  
• Mark G. Kelly, David J. Hand, Niall M. Adams:
  The Impact of Changing Populations on Classifier Performance. 367-371
  
• Wray L. Buntine, Bernd Fischer, Thomas Pressburger:
  Towards Automated Synthesis of Data Mining Programs. 372-376
  
• Gediminas Adomavicius, Alexander Tuzhilin:
  User Profiling in Personalization Applications Through Rule Discovery and Validation. 377-381
  
• Daniel Barbará, Xintao Wu:
  Using Approximations to Scale Exploratory Data Analysis in Datacubes. 382-386
  
• Scott Davies, Andrew W. Moore:
  Bayesian Networks for Lossless Dataset Compression. 387-391
  
• Mihael Ankerst, Christian Elsen, Martin Ester, Hans-Peter Kriegel:
  Visual Classification: An Interactive Approach to Decision Tree Construction. 392-396
  
• Jochen Dörre, Peter Gerstl, Roland Seiffert:
  Text Mining: Finding Nuggets in Mountains of Textual Data. 398-401
  
• Mark Shewhart, Mark Wasson:
  Monitoring a Newsfeed for Hot Topics. 402-404
  
• Jen Que Louie, Tom Kraay:
  Origami: A New Data Visualization Tool. 405-408
  
• Saharon Rosset, Uzi Murad, Einat Neumann, Yizhak Idan, Gadi Pinkas:
  Discovery of Fraud Rules for Telecommunications - Challenges and Solutions. 409-413
  
• H. Kauderer, Gholamreza Nakhaeizadeh, F. Artiles, H. Jeromin:
  Optimization of Collection Efforts in Automobile Financing - a KDD Supported Environment. 414-416
  
• Edgar Hotz, Gholamreza Nakhaeizadeh, B. Petzsche, H. Spiegelberger:
  WAPS, a Data Mining Support Environment for the Planning of Warranty and Goodwill Costs in the Automobile Industry. 417-419
  
• Damianos Chatziantoniou:
  The PanQ Tool and EMF SQL for Complex Data Management. 420-424
  
• John Clear, Debbie Dunn, Brad Harvey, Michael L. Heytens, Peter Lohman, Abhay Mehta, Mark Melton, Lars Rohrberg, Ashok Savasere, Robert M. Wehrmeister, Melody Xu:
  NonStop SQL/MX Primitives for Knowledge Discovery. 425-429
  
• Bing Liu, Wynne Hsu, Yiming Ma, Shu Chen:
  Mining Interesting Knowledge Using DM-II. 430-434