KDD-99

• List of Full Research Papers
• List of Poster Papers

Accepted Research Full Papers:

• A classification-based methodology for planning auditing strategies in fraud detection (#329)
  Francesco Bonchi, Fosca Giannotti, Gianni Mainetto, Dino Pedreschi
• A Statistical Theory for Quantitative Association Rules (#165)
  Yonatan Aumann, Yehuda Lindell
• Activity Monitoring: Noticing interesting changes in behavior (#438)
  Tom Fawcett, Foster Provost
• CACTUS--Clustering Categorical Data Using Summaries (#361)
  Venkatesh Ganti, Johannes Gehrke, Raghu Ramakrishnan
• Compressed Data Cubes for OLAP Aggregate Query Approximation on Continuous Dimensions (#378)
  Jayavel Shanmugasundaram, Usama Fayyad, Paul Bradley
• Density-Based Indexing for Approximate Nearest-Neighbor Queries (#384)
  Kristin Bennett, Usama Fayyad, Dan Geiger
• Discovering Roll-Up Dependencies (#283)
  Jef Wijsen, Raymond T. Ng, Toon Calders
• Efficient Mining of Emerging Patterns:Discovering Trends and Differences (#345)
  Guozhu Dong, Jinyan Li
• Entropy-based Subspace Clustering for Mining Numerical Data (#298)
  Chun-hung Cheng, Ada Wai-chee Fu, Yi Zhang
• Estimating Campaign Benefits and Modeling Lifts (#316)
  Brij Masand, Gregory Piatetsky-Shapiro
• Event Detection From Temporal Data (#197)
  Valery Guralnik, Jaideep Srivastava
• Extending Na�ve Bayes Classifiers using Long Itemsets (#275)
  Dimitris Meretakis, Beat Wuthrich
• Fast and Effective Text Mining Using Linear-time Document Clustering (#393)
  Bjornar Larsen, Chinatsu Aone
• Generalized Additive Neural Networks (#337)
  William Potts
• Horting Hatches an Egg: A New Graph-Theoretic Approach to Collaborative Filtering (#386)
  Charu Aggarwal, Joel Wolf, Kun-Lung Wu, Philip Yu
• Mining GPS Data to Augment Road Models (#367)
  Seth Rogers, Pat Langley, Christopher Wilson
• MetaCost: A General Method for Making Classifiers Cost-Sensitive (#238)
  Pedro Domingos
• Mining in a Data-flow Environment: Experience in Network Intrusion Detection (#414)
  Wenke Lee, Sal Stolfo, Kui Mok
• Mining Optimized Gain Rules for Numeric Attributes (#215)
  Sergei Brin, Rajeev Rastogi, Kyuseok Shim
• Mining the Most Interesting Rules (#369)
  Roberto Bayardo, Rakesh Agrawal
• Optimal Progressive Sampling (#442)
  Foster Provost, David Jensen, Tim Oates
• Pruning and Summarizing the Discovered Associations (#181)
  Bing Liu, Wynne Hsu, Yiming Ma
• Squashing Flat Files Flatter (#263)
  William DuMouchel, Chris Volinsky, Ted Johnson, Corinna Cortes, Daryl Pregibon
• Statistics and Data Mining Techniques for Lifetime Value Modeling (#218)
  D. R. Mani, James Drew, Andrew Betz, Piew Datta
• Trajectory Clustering with Mixtures of Regression Models (#352)
  Scott Gaffney, Padhraic Smyth
• Using a Knowledge Cache for Interactive Discovery of Association Rules (#129)
  Biswadeep Nag, Prasad Deshpande, David DeWitt
• Using Association Rules for Product Assortment Decisions: A Case Study (#149)
  Tom Brijs, Gilbert Swinnen, Koen Vanhoof, Geert Wets

Accepted Research Poster Papers:

• A Study of Support Vectors on Model Independent Example Selection (#286)
  Nadeem Ahmed Syed, Huan Liu, Kah Kay Sung
• Accelerating Exact k-means Algorithms with Geometric Reasoning (#365)
  Dan Pelleg, Andrew Moore
• Adaptive Query Processing for Time-Series Data (#342)
  Yun-Wu Huang, Philip Yu
• An Efficient Algorithm to Update Large Itemsets with Early Pruning (#208)
  Necip Fazil Ayan, Abdullah Uz Tansel, Erol Arkun
• Applying general bayesian techniques to improve TAN induction (#239)
  Jesus Cerquides
• Breaking the Barrier of Transactions: Mining Inter-Transaction Association Rules (#338)
  Anthony Tung, Hongjun Lu, Jiawei Han, Ling Feng
• Detecting Change in Categorical Data: Mining Contrast Sets (#211)
  Stephen Bay, Michael Pazzani
• Evaluating A Class of Distance-Mapping Algorithms for Data Mining and Clustering (#301)
  Jason Wang, Xiong Wang, King-Ip Lin, Dennis Shasha, Bruce Shapiro, Kaizhong Zhang
• Fast Density and Probability Estimation Using CF-Kernel (#356)
  Tian Zhang, Raghu Ramakrishnan, Miron Livny
• Handling Concept Drifts in Incremental Learning with Support Vector Machines (#278)
  Nadeem Ahmed Syed, Huan Liu, Kah Kay Sung
• Identifying Distinctive Subsequences in Multivariate Time Series by Clustering (#357)
  Tim Oates
• Information Mining Platforms: An infrastructure for KDD rapid deployment (#395)
  Corinna Cortes, Daryl Pregibon
• Interestingness Via What Is Not Interesting (#174)
  Sigal Sahar
• Mining Association Rules with Multiple Minimum Supports (#227)
  Bing Liu, Wynne Hsu, Yiming Ma
• Mining features for sequence classification (#314)
  Neal Lesh, Mohammed Zaki, Mitsunori Ogihara
• Mining Lesion-Deficit Associations in a Brain Image Database (#407)
  Vasileios Megalooikonomou, Christos Davatzikos, Edward Herskovits
• On the merits of building categorization systems by supervised clustering (#318)
  Charu Aggarwal, Stephen Gates, Philip Yu
• Prediction with Local Patterns using Cross-Entropy (#430)
  Heikki Mannila, Dimitry Pavlov, Padhraic Smyth
• The Application of AdaBoost for Scalable, Distributed and On-line Learning (#412)
  Wei Fan, Salvatore Stolfo, Junxin Zhang
• The impact of changing populations on classifier performance (#151)
  Mark Kelly, David Hand, Niall Adams
• Towards Automated Synthesis of Data Mining Programs (#200)
  Wray Buntine, Bernd Fischer, Thomas Pressburger
• User Profiling in Personalization Applications through Rule Discovery and Validation (#244)
  Gediminas Adomavicius, Alexander Tuzhilin
• Using approximations to scale exploratory data analysis in datacubes (#188)
  Daniel Barbara, Xintao Wu
• Using Bayesian Networks for Lossless Compression in Data Mining (#392)
  Scott Davies, Andrew Moore
• Visual Classification: An Interactive Approach to Decision Tree Construction (#292)
  Mihael Ankerst, Christian Elsen, Martin Ester, Hans-Peter Kriegel