Day

Time

Sessions

Session 1
(Chair: Don Brown)

• 10:00am - 10:30am
  Feature Mining Algorithms for Scientific Data
• 10:30am - 11:00am
  A comparative study of Anomaly Detection Schemes for Network Intrusion Detection
• 11:00am - 11:30am
  Fast online SVD revisions for lightweight recommender systems
• 11:30am - 12:15pm
  Decision tree classification of spatial data patterns from videokeratography using Zernike polynomials (best paper: 45 mins)

Session 2
(Chair: Inderjit Dhillon)

• 10:00am - 10:30am
  Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
• 10:30am - 11:00am
  Hierarchical Document Clustering Using Frequent Itemsets
• 11:00am - 11:30am
  Scalable, Balanced Model-based Clustering
• 11:30am - 12:00pm
  A New Gravitational Clustering Algorithm
  

• 3:00pm - 3:30pm
  Mining Changes of Classification by Correspondence Tracing
• 3:30pm - 4:00pm
  Dynamic Classification of Online Customers
• 4:00pm - 4:30pm
  
  Communication and Memory Efficient Parallel Decision Tree Construction

• 3:00pm - 3:30pm
  ATLaS: A Native Extension of SQL for Data Mining
• 3:30pm - 4:00pm
  
  Approximate Query Answering by Model Averaging
• 4:00pm - 4:30pm
  On Using Page Cooccurrences for Computing Clickstream Similarity

• 4:45pm - 5:05pm
  ApproxMAP: Approximate Mining of Consensus Sequential Patterns
• 5:05pm - 5:25pm
  Mining frequent sequential patterns under regular expressions: an highly adaptive strategy for pushing constraints
• 5:25pm - 5:45pm
  
  Sort-Merge Feature Selection for Video Data
• 5:45pm - 6:05pm
  
  An Outlier-based Data Association Method for Linking Criminal Incidents

• 4:45pm - 5:05pm
  
  CPAR: Classification based on Predictive Association Rules
• 5:05pm - 5:25pm
  
  Mining Temporal Databases for Subsequence Patterns
• 5:25pm - 5:45pm
  
  Using Low-Memory Representations to Cluster Very Large Data Sets

• Efficient Unsupervised Mining from Noisy Data Sets: Application to Clustering Co-occurrence Data
• Active Sampling: An Effective Approach to Feature Selection
• PageRank, HITS and a Unified Framework for Link Analysis
• The Application of Text Mining Software to Examine Coded Information Applied to Health Outcomes
• Extracting Cyber Communities Through Patterns
  On the Techniques for Data Clustering with Numerical Constraints
• The Analysis of Asthma and Exposure Data
• Using Geographic Information Systems and Data Mining Information
• Detecting Periodicity in Nonideal Datasets
• Detection of Underrepresented Biological Sequences using
  Class-Conditional Distribution Models
• Learning Bayesian Network Structure from Distributed Data
• Mixture models and frequent sets: combining global and local methods for 0-1 data
  Field-theoretic methods for intractable probabilistic models
• Data-Mining of a Large Virtual Community: Relationships Between the Users DB and the Web-Log File
• Cube Lattices: a Framework for Multidimensional Data Mining

Session 7
(Chair: Xintao Wu)

• 10:00am - 10:30am
  
  CloSpan: Mining Closed Sequential Patterns in Large Datasets
• 10:30am - 11:00am
  
  StarClass: Interactive Visual Classification Using Star Coordinates
• 11:00am - 11:30am
  
  Anytime Query-Tuned Kernel Machines Via Cholesky Factorization
• 11:30am - 12:00pm
  
  Estimation of Topological Dimension
  

Session 8
(Chair: Sabyasachi Basu)

• 10:00am - 10:30am
  Generalized Sensitivity Analysis: A Framework for Evaluating Data Analysis Results
• 10:30am - 11:00am
  STAMP: On Discovery of Statistically Important Pattern Repeats in Long Sequential Data
• 11:00am - 11:45am
  Nonparametric Density Estimation: Toward Computational Tractability (best paper: 45 mins)
  
  

• Minisymposium: Multi-Media Data Mining (Pdf)

• Minisymposium: Challenges for data miners, statisticians, and clients (Pdf)
  

• Minisymposium: Multi-Media Data Mining

• Minisymposium: Challenges for data miners, statisticians, and clients (PDFs, Goodman 1, 2, 3, Jordan, Nychka