Conference
Schedule |
Thursday, April 22, 2004 |
7:30am - 8:15am |
Continental Breakfast |
8:15am - 8:30am |
Welcoming Remarks |
8:30am - 9:45am |
Keynote 1 - Christopher M. Bishop (Microsoft Research
Cambridge) Recent Advances in Bayesian Inference Techniques
Session Chair: Michael W. Berry (Univ. of Tennessee) |
9:45am - 10:00am |
Coffee Break |
10:00am - 12:00pm |
Tutorial 1: Top Ten
Data Mining Mistakes - and How to Avoid Them (Elder)
Stream and Sequence Mining
Chair: Sheng Ma (IBM T.J. Watson Research Center):
Mining Relationships Between Interacting Episodes Cancelled
*Carl Mooney*, John Roddick (Flinders U., Australia)
Making Time-series Classification More Accurate using
Learned Constraints
*Chotirat Ratanamahatana*, Eamonn Keogh (U. of California,
Riverside)
GRM: A New Model for Clustering Linear Sequences
Hansheng Lei (SUNY Buffalo)
Non-linear Manifold Learning for Data Stream
*Martin H.C. Law*, Nan Zhang, Anil Jain (U. of Michigan)
Text and Spatial Mining
Chair: William Ferng (The Boeing Company):
Text Mining from Site Invariant and Dependent Features
for Information Extraction Knowledge Adaptation
*Wai Lam*, Tak-Lam Wong (Chinese U. of Hong Kong)
Constructing Time Decompositions for Analyzing Time-stamped
Documents
*Parvathi Chundi* (U. of Nebraska), Daniel Rosenkrantz (SUNY Albany)
Equivalence of Several Two-stage Methods for Linear Discriminant
Analysis
*Peg Howland*, Haesun Park (U. of Minnesota)
A Framework for Discovering Co-location Patterns in Data
Sets with Extended Spatial Objects
*Hui Xiong*, Shashi Shekhar (U. of Minnesota), Yan Huang (U. of
North Texas), Vipin Kumar, Xiaobin Ma, Jin Soung Yoo (U. of Minnesota)
|
12:00pm - 1:45pm |
Lunch (attendees on their own) |
1:45pm - 3:00pm |
Keynote 2 - Sara Graves (University of Alabama in
Huntsville)
Data Mining and Data Usability
Session Chair: Chandrika Kamath (LLNL) |
3:00pm - 4:30pm |
Industry/Government Session
A special session with speakers addressing applications of data mining
to problems of interest to industry as well as those of national interest
(e.g., Homeland Defense) Overview, Boyack, Coughlan, Ma, Meyer
Genomics and Bioinformatics
Chair: Haesun Park (Univ. of Minnesota)
A Top-down Method for Mining Most-specific Frequent Patterns
in Biological Sequences
Martin Ester, *Xiang Zhang* (Simon Fraser U., Canada)
Using Support Vector Machines for Classifying Large Sets
of Multi-represented Objects
Hans-Peter Kriegel, Peer Kroeger, Alexej Pryakhin, *Matthias
Schubert* (U. of Munich, Germany)
Minimum Sum-squared Residue Co-clustering of Gene Expression
Data
*Suvrit Sra*, Yuk Cho, Inderjit Dhillon, Yuqiang Guan (U.
of Texas-Austin)
Scalable Algorithms I
Chair: Hillol Kargupta (Univ. of Maryland, Baltimore County)
Training Support Vector Machines Using Adaptive Clustering
Boley Daniel, *Dongwei Cao* (U. of Minnesota)
IREP++, A Faster Rule Learning Algorithm
*Oliver Dain*, Robert Cunningham, Stephen Boyer (MIT Lincoln
Lab.)
GenIc: A Single-pass Generalized Incremental Algorithm
for Clustering
*Chetan Gupta*, Robert Grossman (U. of Illinois at Chicago)
|
4:30pm - 4:45pm |
Coffee Break |
4:45pm - 5:45pm |
Industry/Government Session continues
Pre-processing and Data Reduction
Chair: Srinivasan Parthasarathy (The Ohio State University)
Conquest: ADistributed Tool for Constructing Summaries
of High-Dimensional Discrete Attribute Data Sets
*Jie Chi*, Mehmet Koyuturk, Ananth Grama (Purdue U.)
Basic Association Rules
*Guichong Li*, Howard Hamilton (U. of Regina, Canada)
Post-processing
Chair: Peg Howland (University of Minnesota)
Hierarchical Clustering for Thematic Browsing and Summarization
of Large Sets of Association Rules
Alipio Jorge (Universidade do Porto, Portugal)
Analytical Evaluation of Clustering Results Using Computational
Negative Controls
*Ronald K. Pearson*, Tom Zylkin, James Schwaber, Gregory
Gonye (Thomas Jefferson U.)
|
6:15pm - 8:00pm |
Poster Session and Welcome Reception |
Friday, April 23, 2004 |
7:30am - 8:15am |
Continental Breakfast |
8:15am - 8:30am |
Welcoming Remarks |
8:30am - 9:45am |
Keynote 3 - C. David Page Jr. (University of Wisconsin
Medical School) Data Mining Research Questions Raised by
Biological Data
Session Chair: David Skillicorn (Queen's University) |
10:00am - 12:00pm |
Tutorial 2: Analyzing Medical Patient
Data: Challenges, Results, and Future Directions (Rao)
Probabilistic/statistical Methods I
Chair: Inderjit Dhillon (Univ. of Texas, Austin)
An Abstract Weighting Framework for Clustering Algorithms
*Richard Nock* (U. Antilles-Guyane), Frank Nielsen (Sony
CS Labs.)
RBA: An Integrated Framework for Regression Based on Association
Rules
*Aysel Ozgur* (U. of Minnesota), Pang Ning Tan (Michigan
State U.), Vipin Kumar (U. of Minnesota
Privacy-preserving Multi-variate Statistical Analysis:
Linear Regression and Classification
*Wenliang Du*, Yunghsiang S. Han (Syracuse U.), Shigang
Chen (U. of Florida)
Clustering with Bregman Divergences
*Arindam Banerjee*, Srujana Merugu, Inderjit Dhillon, Joydeep
Ghosh (U. of Texas-Austin)
Clustering
Chair: Morgan C. Wang (University of Central Florida)
Density-connected Subspace Clustering for High-dimensional
Data
*Peer Kroeger*, Hans-Peter Kriegel, Karin Kailing (U. of
Munich, Germany)
Tesselation and Clustering by Mixture Models and their
Parallel Implementations
*Qiang Du*, Xiaoqiang Wang (Pennsylvania U.)
Clustering Categorical Data using the Correlated-force
Ensemble
*Ming-Syan Chen*, Kun-Ta Chuang (National Taiwan U.)
HICAP: Hierarchical Clustering with Pattern Preservation
*Hui Xiong*, Michael Steinbach (U. of Minnesota), Pang-Ning
Tan (Michigan State U.), Vipin Kumar (U. of Minnesota)
|
12:00pm - 1:45pm |
Lunch (attendees on their own) |
1:45pm - 3:00pm |
Keynote 4 - Ted Senator (Defense Advanced Research
Projects Agency or DARPA) Data Mining for Connecting the
Dots
Session Chair: Umeshwar Dayal (Hewlett-Packard Laboratories) |
3:00pm - 4:30pm |
Tutorial 3: Data Mining for Computer
Security (Brodley, Chan)
Novel Applications
Chair: Sanjay Ranka (University of Florida)
Enhancing Communities of Interest using Bayesian Stochastic
Blockmodels
*Deepak Agrawal*, Darryl Pregibon (AT&T Labs.)
VEDAS: A Mobile and Distributed Data Stream Mining System
for Real-time Vehicle Monitoring
Hillol Kargupta (U. of Maryland, Baltimore County)
DOMISA: DOM-based Information Space Adsorption of Web
Information Hierarchy Mining
Hung-Yu Kao (National Taiwan U.), Jan-Min Ho (Academia Sinica),
*Ming-Syan Chen* (National Taiwan U.)
Scalable Algorithms II
Chair: S. Muthu Muthukrishnan (Rutgers Univ. and AT&T Research)
CREDOS: Classification using Ripple Down Structure (a
case for rare classes)
*Mahesh V. Joshi* (IBM Almaden), Vipin Kumar (U. of Minnesota)
Active Semi-supervision for Pairwise Constrained Clustering
*Sugato Basu*, Arindam Banerjee, Raymond Mooney (U. of
Texas-Austin)
Finding Frequent Patterns in a Large Sparse Graph
*Michihiro Kuramochi*, George Karypis (U. of Minnesota)
|
4:30pm - 4:45pm |
Coffee Break |
4:45pm - 6:15pm |
Tutorial 3 continues Probablistic/statistical
Methods II
Chair: Jacob Kogan (Univ. of Maryland, Baltimore County)
A General Probabilistic Framework for Mining Labeled Ordered
Trees
Nobuhisa Ueda, Kiyoko Aoki, *Hiroshi Mamitsuka* (Kyoto
U, Japan)
Mixture Density Mercer Kernels: A Method to Learn Kernels
Directly from Data
Ashok Srivastava (RIACS/NASA Ames Research Center)
A Mixture Model for Clustering Ensembles
*Alexander Topchy*, Anil Jain, William Punch (Michigan
State U.)
Visual Mining
Chair: Rahul Ramachandran (Univ. of Alabama in Huntsville)
Visualizing RFM Segmentation
Ron Kohavi (Amazon.com), *Rajesh Parekh* (Blue Martini
Software)
Visually Mining through Cluster Hierarchies
Stefan Brechiesen, Hans-Peter Kriegel, *Peer Kroeger*,
Martin Pfeifle (U. of Munich, Germany)
Class-specific Ensembles for Active Learning
*Amit Mandvikar*, Huan Liu (Arizona State U.)
|
Saturday, April 24, 2004 (Workshops) |
7:30am - 8:15am |
Continental Breakfast |
8:30am - 10:00am |
Workshops Begin |
10:00am - 10:30am |
Coffee Break |
10:30am - 12:00pm |
Sessions Resume |
12:00pm - 1:45pm |
Lunch (attendees on their own) |
1:45pm - 3:15pm |
Sessions Resume |
3:15pm - 3:45pm |
Coffee Break |
3:45pm - 5:15pm |
Sessions Resume |
5:15pm |
Conference Adjourns |