KDD-98 Poster Sessions

See Poster Preparation Tips by David Jensen, KDD-98 Poster Sessions Chair

Poster Session 1 (posters 1-24)

Friday, Aug 28, 7:30-9:30 pm
Westside Ballroom, Fifth Floor
(Poster Previews: Fri, 2:30 - 3:00 pm and 3:30 - 4:00 pm,
Westside Ballroom, Fifth Floor)

1. Online Generation of Profile Association Rules
   Charu C. Aggarwal, T. J. Watson Research Center; Zheng Sun, Duke University; Philip S. Yu, T. J. Watson Research Center
2. ADtrees for Fast Counting and for Fast Learning of Association Rules
   Brigham Anderson and Andrew Moore, Carnegie Mellon University
3. Independence Diagrams: A Technique for Visual Data Mining
   Stefan Berchtold and H. V. Jagadish, AT&T Laboratories; Kenneth A. Ross, Columbia University
4. Direct Marketing Response Models Using Genetic Algorithms
   Siddhartha Bhattacharyya, University of Illinois at Chicago
5. Mining Association Rules in Hypertext Databases
   José Borges and Mark Levene, University College London
6. Blurring the Distinction between Command and Data in Scientific KDD
   John Carlis, Elizabeth Shoop and Scott Krieger, University of Minnesota
7. Probabilistic Modeling for Information Retrieval with Unsupervised Training Data
   Ernest P. Chan, Credit Suisse First Boston; Santiago Garcia, Morgan Stanley & Co. Inc.; Salim Roukos, IBM T. J. Watson Research Center
8. Toward Scalable Learning with Non-Uniform Class and Cost Distributions: A Case Study in Credit Card Fraud Detection
   Philip K. Chan, Florida Institute of Technology and Salvatore J. Stolfo, Columbia University
9. Joins that Generalize: Text Classification Using WHIRL
   William W. Cohen, AT&T Labs-Research and Haym Hirsh, Rutgers University
10. Giga-Mining
    Corinna Cortes and Daryl Pregibon, AT&T Labs-Research
11. Interactive Interpretation of Kohonen Maps Applied to Curves
    Anne Debregeas and Georges Hebrail, Electricite de France
12. FlexiMine - A Flexible Platform for KDD Research and Application Construction
    C. Domshlak, D. Gershkovich, E. Gudes, N. Liusternik, A. Meisels, T. Rosen and S. E. Shimony, Ben-Gurion University
13. A Fast Computer Intrusion Detection Algorithm Based on Hypothesis Testing of Command Transition Probabilities
    William DuMouchel, AT&T Labs-Research and Matthias Schonlau, AT&T Labs-Research and National Institute of Statistical Sciences
14. Initialization of Iterative Refinement Clustering Algorithms
    Usama Fayyad, Cory Reina and P. S. Bradley, Microsoft Research
15. Mining in the Presence of Selectivity Bias and its Application to Reject Inference
    A. J. Feelders, Tilburg University; Soong Chang and G. J. McLachlan, University of Queensland
16. On the Efficient Gathering of Sufficient Statistics for Classification from Large SQL Databases
    Goetz Graefe, Usama Fayyad and Surajit Chaudhuri, Microsoft Corporation
17. Coactive Learning for Distributed Data Mining
    Dan L. Grecu and Lee A. Becker, Worcester Polytechnic Institute
18. Mining Segment-Wise Periodic Patterns in Time-Related Databases
    Jiawei Han, Wan Gong and Yiwen Yin, Simon Fraser University
19. Learning to Predict the Duration of an Automoblie Trip
    Simon Handley and Pat Langley, Daimler-Benz Research and Technology Center; Folke A. Rauscher, Daimler-Benz AG
20. Fast Computation of 2-Dimensional Depth Contours
    Ted Johnson, AT&T Research Center; Ivy Kwok and Raymond Ng, University of British Columbia
21. Comparing Massive High-Dimensional Data Sets
    Theodore Johnson and Tamraparni Dasu, AT&T Labs-Research
22. Defining the Goals to Optimise Data Mining Performance
    Mark G. Kelly, David J. Hand and Niall M. Adams, The Open University
23. An Enhanced Representation of Time Series which Allows Fast and Accurate Classification, Clustering and Relevance Feedback
    Eamonn J. Keogh and Michael J. Pazzani, University of California, Irvine
24. Active Templates: Comprehensive Support for the Knowledge Discovery Process
    Randy Kerber, Hal Beck, Tej Anand and Bill Smart, NCR Human Interface Technology Center

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    Poster Session 2 (25-49)

    Saturday, Aug 29, 7:30-9:30 pm
    Broadway North and South, Sixth Floor
    (Poster Previews: Sat, 12:00 - 12:30 pm and 4:30 - 5:00 pm, Westside Ballroom, Fifth Floor)

25. Targeting Business Users with Decision Table Classifiers
    Ron Kohavi and Daniel Sommerfield, Silicon Graphics, Inc.
26. BAYDA: Software for Bayesian Classification and Feature Selection
    Petri Kontkanen, Petri Myllymäki, Tomi Silander and Henry Tirri, University of Helsinki
27. Approaches to Online Learning and Concept Drift for User Identification in Computer Security
    Terran Lane and Carla E. Brodley, Purdue University
28. Human Performance on Clustering Web Pages: A Preliminary Study
    Sofus A. Macskassy, Arunava Banerjee, Brian D. Davison and Haym Hirsh, The State University of New Jersey
29. Aggregation of Imprecise and Uncertain Information for Knowledge Discovery in Databases
    Sally McClean, Bryan Scotney and Mary Shapcott, University of Ulster
30. Discovering Predictive Association Rules
    Nimrod Megiddo and Ramakrishnan Srikant, IBM Almaden Research Center
31. Reinforcement Learning for Trading Systems and Portfolios
    John Moody and Matthew Saffell, Oregon Graduate Institute
32. Group Bitmap Index: A Structure for Association Rules Retrieval
    Tadeusz Morzy and Maciej Zakrzewicz, Poznan University of Technology
33. Towards Personalization of Algorithms Evaluation in Data Mining
    Gholamreza Nakhaeizadeh, Daimler-Benz AG and Alexander Schnabl, Technical University Vienna
34. Large Datasets Lead to Overly Complex Models: An Explanation and a Solution
    Tim Oates and David Jensen, University of Massachusetts
35. Analysing Rock Samples for the Mars Lander
    Jonathan Oliver, University of California, Berkeley; Ted Roush and Paul Gazis, NASA Ames Research Center; Wray Buntine, Rohan Baxter and Steve Waterhouse, Ultimode Systems
36. Memory Placement Techniques for Parallel Association Mining
    Srinivasan Parthasarathy, Mohammed J. Zaki and Wei Li, University of Rochester
37. Methods for Linking and Mining Massive Heterogeneous Databases
    José C. Pinheiro and Don X. Sun, Bell Laboratories
38. Mining Databases with Different Schemas: Integrating Incompatible Classifiers
    Andreas L. Prodromidis and Salvatore Stolfo, Columbia University
39. Time Series Forecasting from High-Dimensional Data with Multiple Adaptive Layers
    R. Bharat Rao, Scott Rickard and Frans Coetzee, Siemens Corporate Research, Inc.
40. Ranking - Methods for Flexible Evaluation and Efficient Comparison of Classification Performance
    Saharon Rosset, Tel Aviv University
41. A Robust System Architecture for Mining Semi-Structured Data
    Lisa Singh, Bin Chen, Rebecca Haight, Peter Scheuermann and Kiyoko Aoki, Northwestern University
42. Defining diff as a Data Mining Primitive
    Ramesh Subramonian, Intel Corporation
43. Simultaneous Reliability Evaluation of Generality and Accuracy for Rule Discovery in Databases
    Einoshin Suzuki, Yokohama National University
44. Mining Generalized Association Rules and Sequential Patterns Using SQL Queries
    Shiby Thomas, University of Florida and Sunita Sarawagi, IBM Almaden Research Center
45. Data Reduction Based on Hyper Relations
    Hui Wang, Ivo Düntsch and David Bell, University of Ulster
46. Discovering Technical Traders in the T-bond Futures Market
    Andreas S. Weigend, Fei Chen and Stephen Figlewski, New York University; Steven R. Waterhouse, Ultimode Systems
47. Learning to Predict Rare Events in Event Sequences
    Gary M. Weiss, AT&T Labs and Rutgers University and Haym Hirsh, Rutgers University
48. Daily Prediction of Major Stock Indices from Textual WWW Data
    B. Wüthrich, D. Permunetilleke, S. Leung, V. Cho, and J. Zhang, The Hong Kong University of Science and Technology; W. Lam, The Chinese University of Hong Kong
49. PLANMINE: Sequence Mining for Plan Failures
    Mohammed J. Zaki, Neal Lesh and Mitsunori Ogihara, University of Rochester