5. KDD 1999:
San Diego,
CA,
USA
Proceedings of the Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining,
August 15-18,
1999,
San Diego,
CA,
USA. ACM,
1999
- Rakesh Agrawal:
Data Mining: Crossing the Chasm (Invited talk, Abstract only).
2
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- Richard D. Hackathorn:
Farming the Web for Systematic Business Intelligence (Invited talk, Abstract only).
3
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- Daryl Pregibon:
2001: A Statistical Odyssey (Invited talk, Abstract only).
4
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- William DuMouchel, Chris Volinsky, Theodore Johnson, Corinna Cortes, Daryl Pregibon:
Squashing Flat Files Flatter.
6-15
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- Bjornar Larsen, Chinatsu Aone:
Fast and Effective Text Mining Using Linear-Time Document Clustering.
16-22
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- Foster J. Provost, David Jensen, Tim Oates:
Efficient Progressive Sampling.
23-32
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- Valery Guralnik, Jaideep Srivastava:
Event Detection from Time Series Data.
33-42
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- Guozhu Dong, Jinyan Li:
Efficient Mining of Emerging Patterns: Discovering Trends and Differences.
43-52
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- Tom Fawcett, Foster J. Provost:
Activity Monitoring: Noticing Interesting Changes in Behavior.
53-62
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- Scott Gaffney, Padhraic Smyth:
Trajectory Clustering with Mixtures of Regression Models.
63-72
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- Venkatesh Ganti, Johannes Gehrke, Raghu Ramakrishnan:
CACTUS - Clustering Categorical Data Using Summaries.
73-83
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- Chun Hung Cheng, Ada Wai-Chee Fu, Yi Zhang:
Entropy-based Subspace Clustering for Mining Numerical Data.
84-93
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- D. R. Mani, James Drew, Andrew Betz, Piew Datta:
Statistics and Data Mining Techniques for Lifetime Value Modeling.
94-103
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- Seth Rogers, Pat Langley, Christopher Wilson:
Mining GPS Data to Augment Road Models.
104-113
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- Wenke Lee, Salvatore J. Stolfo, Kui W. Mok:
Mining in a Data-Flow Environment: Experience in Network Intrusion Detection.
114-124
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- Bing Liu, Wynne Hsu, Yiming Ma:
Pruning and Summarizing the Discovered Associations.
125-134
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- Sergey Brin, Rajeev Rastogi, Kyuseok Shim:
Mining Optimized Gain Rules for Numeric Attributes.
135-144
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- Roberto J. Bayardo Jr., Rakesh Agrawal:
Mining the Most Interesting Rules.
145-154
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- Pedro Domingos:
MetaCost: A General Method for Making Classifiers Cost-Sensitive.
155-164
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- Dimitris Meretakis, Beat Wüthrich:
Extending Naïve Bayes Classifiers Using Long Itemsets.
165-174
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- Francesco Bonchi, Fosca Giannotti, Gianni Mainetto, Dino Pedreschi:
A Classification-Based Methodology for Planning Audit Strategies in Fraud Detection.
175-184
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- Gregory Piatetsky-Shapiro, Brij M. Masand:
Estimating Campaign Benefits and Modeling Lift.
185-193
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- William J. E. Potts:
Generalized Additive Neural Networks.
194-200
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- 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
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- Jef Wijsen, Raymond T. Ng, Toon Calders:
Discovering Roll-Up Dependencies.
213-222
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- Jayavel Shanmugasundaram, Usama M. Fayyad, Paul S. Bradley:
Compressed Data Cubes for OLAP Aggregate Query Approximation on Continuous Dimensions.
223-232
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- Kristin P. Bennett, Usama M. Fayyad, Dan Geiger:
Density-Based Indexing for Approximate Nearest-Neighbor Queries.
233-243
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- Biswadeep Nag, Prasad Deshpande, David J. DeWitt:
Using a Knowledge Cache for Interactive Discovery of Association Rules.
244-253
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- Tom Brijs, Gilbert Swinnen, Koen Vanhoof, Geert Wets:
Using Association Rules for Product Assortment Decisions: A Case Study.
254-260
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- Yonatan Aumann, Yehuda Lindell:
A Statistical Theory for Quantitative Association Rules.
261-270
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- Nadeem Ahmed Syed, Huan Liu, Kah Kay Sung:
A Study of Support Vectors on Model Independent Example Selection.
272-276
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- Dan Pelleg, Andrew W. Moore:
Accelerating Exact k-means Algorithms with Geometric Reasoning.
277-281
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- Yun-Wu Huang, Philip S. Yu:
Adaptive Query Processing for Time-Series Data.
282-286
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- Necip Fazil Ayan, Abdullah Uz Tansel, M. Erol Arkun:
An Efficient Algorithm to Update Large Itemsets with Early Pruning.
287-291
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- Jesús Cerquides:
Applying General Bayesian Techniques to Improve TAN Induction.
292-296
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- Anthony K. H. Tung, Hongjun Lu, Jiawei Han, Ling Feng:
Breaking the Barrier of Transactions: Mining Inter-Transaction Association Rules.
297-301
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- Stephen D. Bay, Michael J. Pazzani:
Detecting Change in Categorical Data: Mining Contrast Sets.
302-306
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- 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
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- Tian Zhang, Raghu Ramakrishnan, Miron Livny:
Fast Density Estimation Using CF-Kernel for Very Large Databases.
312-316
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- Nadeem Ahmed Syed, Huan Liu, Kah Kay Sung:
Handling Concept Drifts in Incremental Learning with Support Vector Machines.
317-321
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- Tim Oates:
Identifying Distinctive Subsequences in Multivariate Time Series by Clustering.
322-326
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- Corinna Cortes, Daryl Pregibon:
Information Mining Platforms: An Infrastructure for KDD Rapid Deployment.
327-331
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- Sigal Sahar:
Interestingness via What is Not Interesting.
332-336
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- Bing Liu, Wynne Hsu, Yiming Ma:
Mining Association Rules with Multiple Minimum Supports.
337-341
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- Neal Lesh, Mohammed Javeed Zaki, Mitsunori Ogihara:
Mining Features for Sequence Classification.
342-346
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- Vasileios Megalooikonomou, Christos Davatzikos, Edward Herskovits:
Mining Lesion-Deficit Associations in a Brain Image Database.
347-351
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- Charu C. Aggarwal, Stephen C. Gates, Philip S. Yu:
On the Merits of Building Categorization Systems by Supervised Clustering.
352-356
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- Heikki Mannila, Dmitry Pavlov, Padhraic Smyth:
Prediction with Local Patterns using Cross-Entropy.
357-361
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- Wei Fan, Salvatore J. Stolfo, Junxin Zhang:
The Application of AdaBoost for Distributed, Scalable and On-Line Learning.
362-366
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- Mark G. Kelly, David J. Hand, Niall M. Adams:
The Impact of Changing Populations on Classifier Performance.
367-371
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- Wray L. Buntine, Bernd Fischer, Thomas Pressburger:
Towards Automated Synthesis of Data Mining Programs.
372-376
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- Gediminas Adomavicius, Alexander Tuzhilin:
User Profiling in Personalization Applications Through Rule Discovery and Validation.
377-381
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- Daniel Barbará, Xintao Wu:
Using Approximations to Scale Exploratory Data Analysis in Datacubes.
382-386
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- Scott Davies, Andrew W. Moore:
Bayesian Networks for Lossless Dataset Compression.
387-391
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- Mihael Ankerst, Christian Elsen, Martin Ester, Hans-Peter Kriegel:
Visual Classification: An Interactive Approach to Decision Tree Construction.
392-396
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- Jochen Dörre, Peter Gerstl, Roland Seiffert:
Text Mining: Finding Nuggets in Mountains of Textual Data.
398-401
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- Mark Shewhart, Mark Wasson:
Monitoring a Newsfeed for Hot Topics.
402-404
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- Jen Que Louie, Tom Kraay:
Origami: A New Data Visualization Tool.
405-408
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- Saharon Rosset, Uzi Murad, Einat Neumann, Yizhak Idan, Gadi Pinkas:
Discovery of Fraud Rules for Telecommunications - Challenges and Solutions.
409-413
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- H. Kauderer, Gholamreza Nakhaeizadeh, F. Artiles, H. Jeromin:
Optimization of Collection Efforts in Automobile Financing - a KDD Supported Environment.
414-416
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- 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
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- Damianos Chatziantoniou:
The PanQ Tool and EMF SQL for Complex Data Management.
420-424
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- 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
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- Bing Liu, Wynne Hsu, Yiming Ma, Shu Chen:
Mining Interesting Knowledge Using DM-II.
430-434
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Copyright © Sat May 16 23:27:54 2009
by Michael Ley (ley@uni-trier.de)
