4. KDD 1998:
New York City,
New York,
USA
Rakesh Agrawal,
Paul E. Stolorz,
Gregory Piatetsky-Shapiro (Ed.):
Proceedings of the Fourth International Conference on Knowledge Discovery and Data Mining (KDD-98),
August 27-31,
1998,
New York City,
New York,
USA. AAAI Press,
1998,
ISBN 1-57735-070-7
Technical Papers
- Khaled Alsabti, Sanjay Ranka, Vineet Singh:
CLOUDS: A Decision Tree Classifier for Large Datasets.
2-8
- Paul S. Bradley, Usama M. Fayyad, Cory Reina:
Scaling Clustering Algorithms to Large Databases.
9-15
- Gautam Das, King-Ip Lin, Heikki Mannila, Gopal Renganathan, Padhraic Smyth:
Rule Discovery from Time Series.
16-22
- Gautam Das, Heikki Mannila, Pirjo Ronkainen:
Similarity of Attributes by External Probes.
23-29
- Luc Dehaspe, Hannu Toivonen, Ross D. King:
Finding Frequent Substructures in Chemical Compounds.
30-36
- Pedro Domingos:
Occam's Two Razors: The Sharp and the Blunt.
37-43
- Martin Ester, Alexander Frommelt, Hans-Peter Kriegel, Jörg Sander:
Algorithms for Characterization and Trend Detection in Spatial Databases.
44-50
- Valery Guralnik, Duminda Wijesekera, Jaideep Srivastava:
Pattern Directed Mining of Sequence Data.
51-57
- Alexander Hinneburg, Daniel A. Keim:
An Efficient Approach to Clustering in Large Multimedia Databases with Noise.
58-65
- Wenke Lee, Salvatore J. Stolfo, Kui W. Mok:
Mining Audit Data to Build Intrusion Detection Models.
66-72
- Charles X. Ling, Chenghui Li:
Data Mining for Direct Marketing: Problems and Solutions.
73-79
- Bing Liu, Wynne Hsu, Yiming Ma:
Integrating Classification and Association Rule Mining.
80-86
- Gholamreza Nakhaeizadeh, Charles Taylor, Carsten Lanquillon:
Evaluating Usefulness for Dynamic Classification.
87-93
- Balaji Padmanabhan, Alexander Tuzhilin:
A Belief-Driven Method for Discovering Unexpected Patterns.
94-100
- Greg Ridgeway, David Madigan, Thomas Richardson, John O'Kane:
Interpretable Boosted Naïve Bayes Classification.
101-104
- Martin Staudt, Jörg-Uwe Kietz, Ulrich Reimer:
A Data Mining Support Environment and its Application on Insurance Data.
105-111
- Evan W. Steeg, Derek A. Robinson, Ed Willis:
Coincidence Detection: A Fast Method for Discovering Higher-Order Correlations in Multidimensional Data.
112-120
- Ke Wang, Soon Hock William Tay, Bing Liu:
Interestingness-Based Interval Merger for Numeric Association Rules.
121-128
Poster Papers
- Charu C. Aggarwal, Zheng Sun, Philip S. Yu:
Online Generation of Profile Association Rules.
129-133
- Brigham S. Anderson, Andrew W. Moore:
ADtrees for Fast Counting and for Fast Learning of Association Rules.
134-138
- Stefan Berchtold, H. V. Jagadish, Kenneth A. Ross:
Independence Diagrams: A Technique for Visual Data Mining.
139-143
- Siddhartha Bhattacharyya:
Direct Marketing Response Models Using Genetic Algorithms.
144-148
- José Borges, Mark Levene:
Mining Association Rules in Hypertext Databases.
149-153
- John V. Carlis, Elizabeth Shoop, Scott Krieger:
Blurring the Distinction between Command and Data in Scientific KDD.
154-158
- Ernest P. Chan, Santiago Garcia, Salim Roukos:
Probabilistic Modeling for Information Retrieval with Unsupervised Training Data.
159-163
- Philip K. Chan, Salvatore J. Stolfo:
Toward Scalable Learning with Non-Uniform Class and Cost Distributions: A Case Study in Credit Card Fraud Detection.
164-168
- William W. Cohen, Haym Hirsh:
Joins that Generalize: Text Classification Using WHIRL.
169-173
- Corinna Cortes, Daryl Pregibon:
Giga-Mining.
174-178
- Anne Debregeas, Georges Hébrail:
Interactive Interpretation of Kohonen Maps Applied to Curves.
179-183
- Carmel Domshlak, D. Gershkovich, Ehud Gudes, N. Liusternik, Amnon Meisels, Tzachi Rosen, Solomon Eyal Shimony:
FlexiMine - A Flexible Platform for KDD Research and Application Construction.
184-188
- William DuMouchel, Matthias Schonlau:
A Fast Computer Intrusion Detection Algorithm Based on Hypothesis Testing of Command Transition Probabilities.
189-193
- Usama M. Fayyad, Cory Reina, Paul S. Bradley:
Initialization of Iterative Refinement Clustering Algorithms.
194-198
- A. J. Feelders, Soong Chang, Geoffrey J. McLachlan:
Mining in the Presence of Selectivity Bias and its Application to Reject Inference.
199-203
- Goetz Graefe, Usama M. Fayyad, Surajit Chaudhuri:
On the Efficient Gathering of Sufficient Statistics for Classification from Large SQL Databases.
204-208
- Dan L. Grecu, Lee A. Becker:
Coactive Learning for Distributed Data Mining.
209-213
- Jiawei Han, Wan Gong, Yiwen Yin:
Mining Segment-Wise Periodic Patterns in Time-Related Databases.
214-218
- Simon Handley, Pat Langley, Folke A. Rauscher:
Learning to Predict the Duration of an Automobile Trip.
219-223
- Theodore Johnson, Ivy Kwok, Raymond T. Ng:
Fast Computation of 2-Dimensional Depth Contours.
224-228
- Theodore Johnson, Tamraparni Dasu:
Comparing Massive High-Dimensional Data Sets.
229-233
- Mark G. Kelly, David J. Hand, Niall M. Adams:
Defining the Goals to Optimise Data Mining Performance.
234-238
- Eamonn J. Keogh, Michael J. Pazzani:
An Enhanced Representation of Time Series Which Allows Fast and Accurate Classification, Clustering and Relevance Feedback.
239-243
- Randy Kerber, Hal Beck, Tej Anand, Bill Smart:
Active Templates: Comprehensive Support for the Knowledge Discovery Process.
244-248
- Ron Kohavi, Dan Sommerfield:
Targeting Business Users with Decision Table Classifiers.
249-253
- Petri Kontkanen, Petri Myllymäki, Tomi Silander, Henry Tirri:
BAYDA: Software for Bayesian Classification and Feature Selection.
254-258
- Terran Lane, Carla E. Brodley:
Approaches to Online Learning and Concept Drift for User Identification in Computer Security.
259-263
- Sofus A. Macskassy, Arunava Banerjee, Brian D. Davison, Haym Hirsh:
Human Performance on Clustering Web Pages: A Preliminary Study.
264-268
- Sally I. McClean, Bryan W. Scotney, Mary Shapcott:
Aggregation of Imprecise and Uncertain Information for Knowledge Discovery in Databases.
269-273
- Nimrod Megiddo, Ramakrishnan Srikant:
Discovering Predictive Association Rules.
274-278
- John E. Moody, Matthew Saffell:
Reinforcement Learning for Trading Systems and Portfolios.
279-283
- Tadeusz Morzy, Maciej Zakrzewicz:
Group Bitmap Index: A Structure for Association Rules Retrieval.
284-288
- Gholamreza Nakhaeizadeh, Alexander Schnabl:
Towards the Personalization of Algorithms Evaluation in Data Mining.
289-293
- Tim Oates, David Jensen:
Large Datasets Lead to Overly Complex Models: An Explanation and a Solution.
294-298
- Jonathan J. Oliver, Ted Roush, Paul Gazis, Wray L. Buntine, Rohan A. Baxter, Steven R. Waterhouse:
Analysing Rock Samples for the Mars Lander.
299-303
- Srinivasan Parthasarathy, Mohammed Javeed Zaki, Wei Li:
Memory Placement Techniques for Parallel Association Mining.
304-308
- José C. Pinheiro, Don X. Sun:
Methods for Linking and Mining Massive Heterogeneous Databases.
309-313
- Andreas L. Prodromidis, Salvatore J. Stolfo:
Mining Databases with Different Schemas: Integrating Incompatible Classifiers.
314-318
- R. Bharat Rao, Scott Rickard, Frans Coetzee:
Time Series Forecasting from High-Dimensional Data with Multiple Adaptive Layers.
319-323
- Saharon Rosset:
Ranking - Methods for Flexible Evaluation and Efficient Comparison of Classification Performance.
324-328
- Lisa Singh, Bin Chen, Rebecca Haight, Peter Scheuermann, Kiyoko Aoki:
A Robust System Architecture for Mining Semi-Structured Data.
329-333
- Ramesh Subramonian:
Defining diff as a Data Mining Primitive.
334-338
- Einoshin Suzuki:
Simultaneous Reliability Evaluation of Generality and Accuracy for Rule Discovery in Databases.
339-343
- Shiby Thomas, Sunita Sarawagi:
Mining Generalized Association Rules and Sequential Patterns Using SQL Queries.
344-348
- Hui Wang, Ivo Düntsch, David A. Bell:
Data Reduction Based on Hyper Relations.
349-353
- Andreas S. Weigend, Fei Chen, Stephen Figlewski, Steven R. Waterhouse:
Discovering Technical Traders in the T-bond Futures Market.
354-358
- Gary M. Weiss, Haym Hirsh:
Learning to Predict Rare Events in Event Sequences.
359-363
- Beat Wüthrich, D. Permunetilleke, S. Leung, Vincent Cho, Jian Zhang, W. Lam:
Daily Prediction of Major Stock Indices from Textual WWW Data.
364-368
- Mohammed Javeed Zaki, Neal Lesh, Mitsunori Ogihara:
PlanMine: Sequence Mining for Plan Failures.
369-374
Conference Report
Copyright © Fri Mar 12 17:18:01 2010
by Michael Ley (ley@uni-trier.de)
