6. KDD 2000:
Boston, MA, USA
Raghu Ramakrishnan, Salvatore J. Stolfo, Roberto J. Bayardo, Ismail Parsa (Eds.):
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining, Boston, MA, USA, August 20-23, 2000.
ACM 2000, ISBN 1-58113-233-6
- Christos H. Papadimitriou:
On certain rigorous approaches to data mining (invited talk, abstract only).
- Bruce G. Buchanan:
Informed knowledge discovery: using prior knowledge in discovery programs (invited talk, abstract only).
- Jason Catlett:
Among those dark electronic mills: privacy and data mining (invited talk, abstract only).
- James Goodnight:
Decision support in the booming e-world (invited talk, abstract only).
- Matt Cutler:
E-metrics: tomorrow's business metrics today (invited talk, abstract only).
- David Stodder:
After the gold rush (invited talk, abstract only): data mining in the new economy (invited talk, abstract only).
- Corinna Cortes, Kathleen Fisher, Daryl Pregibon, Anne Rogers:
Hancock: a language for extracting signatures from data streams.
- Tony Fountain, Thomas G. Dietterich, Bill Sudyka:
Mining IC test data to optimize VLSI testing.
Constraints and Evaluation in the KDD Process
- Douglas A. Talbert, Douglas H. Fisher:
An empirical analysis of techniques for constructing and searching k-dimensional trees.
- Mohammed Javeed Zaki:
Generating non-redundant association rules.
- Ted E. Senator:
Ongoing management and application of discovered knowledge in a large regulatory organization: a case study of the use and impact of NASD Regulation's Advanced Detection System (RADS).
- Balaji Padmanabhan, Alexander Tuzhilin:
Small is beautiful: discovering the minimal set of unexpected patterns.
New KDD Algorithms
Efficiency and Scalability of KDD Algorithms
Mining the Web
Interactive Knowledge Exploration
- William W. Cohen, Henry A. Kautz, David A. McAllester:
Hardening soft information sources.
- Daniel Barbará, Ping Chen:
Using the fractal dimension to cluster datasets.
- Ke Wang, Senqiang Zhou, Yu He:
Growing decision trees on support-less association rules.
- Wei Wang, Jiong Yang, Philip S. Yu:
Efficient mining of weighted association rules (WAR).
- Jiong Yang, Wei Wang, Philip S. Yu:
Mining asynchronous periodic patterns in time series data.
- Igor V. Cadez, David Heckerman, Christopher Meek, Padhraic Smyth, Steven White:
Visualization of navigation patterns on a Web site using model-based clustering.
- Eamonn J. Keogh, Michael J. Pazzani:
Scaling up dynamic time warping for datamining applications.
- Mong-Li Lee, Tok Wang Ling, Wai Lup Low:
IntelliClean: a knowledge-based intelligent data cleaner.
- Dmitry Pavlov, Darya Chudova, Padhraic Smyth:
Towards scalable support vector machines using squashing.
- Tom Brijs, Bart Goethals, Gilbert Swinnen, Koen Vanhoof, Geert Wets:
A data mining framework for optimal product selection in retail supermarket data: the generalized PROFSET model.
- Jason Tsong-Li Wang, Qicheng Ma, Dennis Shasha, Cathy H. Wu:
Application of neural networks to biological data mining: a case study in protein sequence classification.
- Xiuzhen Zhang, Guozhu Dong, Kotagiri Ramamohanarao:
Exploring constraints to efficiently mine emerging patterns from large high-dimensional datasets.
- Stephen D. Bay:
Multivariate discretization of continuous variables for set mining.
- Kenji Yamanishi, Jun-ichi Takeuchi, Graham J. Williams, Peter Milne:
On-line unsupervised outlier detection using finite mixtures with discounting learning algorithms.
- Petri Kontkanen, Jussi Lahtinen, Petri Myllymäki, Henry Tirri:
Unsupervised Bayesian visualization of high-dimensional data.
- Tobias Scheffer, Stefan Wrobel:
A sequential sampling algorithm for a general class of utility criteria.
- Minos N. Garofalakis, Dongjoon Hyun, Rajeev Rastogi, Kyuseok Shim:
Efficient algorithms for constructing decision trees with constraints.
- Jeonghee Yi, Neel Sundaresan:
A classifier for semi-structured documents.
- Dennis DeCoste, Kiri Wagstaff:
Alpha seeding for support vector machines.
- Jian Pei, Jiawei Han:
Can we push more constraints into frequent pattern mining?
- Jiawei Han, Jian Pei, Behzad Mortazavi-Asl, Qiming Chen, Umeshwar Dayal, Meichun Hsu:
FreeSpan: frequent pattern-projected sequential pattern mining.
- Jennifer G. Dy, Carla E. Brodley:
Visualization and interactive feature selection for unsupervised data.
- YongSeog Kim, W. Nick Street, Filippo Menczer:
Feature selection in unsupervised learning via evolutionary search.
- Alfred Inselberg, Tova Avidan:
Classification and visualization for high-dimensional data.
Text Mining and Data Preparation
E-Commerce and Temporal Data
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- Rónán Páircéir, Sally I. McClean, Bryan W. Scotney:
Discovery of multi-level rules and exceptions from a distributed database.
- Ron Kohavi, Myra Spiliopoulou, Jaideep Srivastava:
Web mining for e-commerce (workshop session - title only).
- Hillol Kargupta, Philip Chan, Vipin Kumar, Zoran Obradovic:
Distributed and parallel knowledge discovery (workshop session - title only).
- Simeon J. Simoff, Osmar R. Zaïane:
Multimedia data mining (workshop session - title only).
- Marko Grobelnik, Dunja Mladenic, Natasa Milic-Frayling:
Text mining (workshop session - title only).