WhatToSee

Index of KDD 2002

• A Model for Discovering Customer Value for E-Content
• A Robust and Efficient Clustering Algorithm based on Cohesion Self-Merging
• A Unifying Framework for Detecting Outliers and Change Points from Non-Stationary Time Series Data
• ANF: A Fast and Scalable Tool for Data Mining in Massive GraphsChristopher R. Palmer Computer Science Dept Carnegie Mellon University Pittsburgh, PA crpalmer@ cs.cmu.edu
• B-EM: A Classifier Incorporating Bootstrap with EM Approach for Data Mining
• Bayesian analysis of massive datasets via particle filters
• Bursty and Hierarchical Structure in Streams
• CVS: A Correlation-Verification Based Smoothing Technique on Information Retrieval and Term Clustering
• Clustering Seasonality Patterns in the Presence of Errors
• Collaborative Crawling: Mining User Experiences for Topical Resource Discovery
• Collusion in The U.S. Crop Insurance Program: Applied Data Mining
• Combining Clustering and Co-training to Enhance Text Classification Using Unlabelled Data
• Construct robust rule sets for classification
• Discovering Informative Content Blocks from Web Documents
• Discovering Word Senses from Text
• DualMiner: A Dual-Pruning Algorithm for Itemsets with Constraints
• Efficient Handling of High-Dimensional Feature Spaces by Randomized Classifier Ensembles
• Efficiently Mining Frequent Trees in a Forest
• Enhanced Word Clustering for Hierarchical Text Classification
• Evaluating Classifiers' Performance In A Constrained Environment
• Exploiting Response Models -Optimizing Cross-Sell and Up-Sell Opportunities in Banking
• Exploiting Unlabeled Data in Ensemble Methods
• Extracting Decision Trees From Trained Neural Networks
• Finding Surprising Patterns in a Time Series Database in Linear Time and Space
• Frequent Term-Based Text Clustering
• From Run-time Behavior to Usage Scenarios: An Interaction-Pattern Mining Approach
• Handling Very Large Numbers of Association Rules in the Analysis of Microarray Data
• Hierarchical Model-Based Clustering of Large Datasets Through Fractionation and Refractionation.
• Incremental Context Mining for Adaptive Document Classification
• Interactive Deduplication using Active Learning
• Learning Domain-Independent String Transformation Weights for High Accuracy Object Identification
• Learning Nonstationary Models of Normal Network Traffic for Detecting Novel Attacks
• Learning to Match and Cluster Large High-Dimensional Data Sets For Data Integration
• MARK: A Boosting Algorithm for Heterogeneous Kernel Models
• Making every bit count: Fast nonlinear axis scaling
• Mining Complex Models from Arbitrarily Large Databases in Constant Time
• Mining Frequent Item Sets by Opportunistic Projection"
• Mining Heterogeneous Gene Expression Data with Time Lagged Recurrent Neural Networks
• Mining Intrusion Detection Alarms for Actionable Knowledge
• Mining Knowledge-Sharing Sites for Viral Marketing
• Mining Product Reputations on the Web
• Non-Linear Dimensionality Reduction Techniques for Classification and Visualization
• On Effective Classification of Strings with Wavelets
• On the Need for Time Series Data Mining Benchmarks: A Survey and Empirical Demonstration
• On the potential of domain literature for clustering and Bayesian network learning
• Optimizing Search Engines using Clickthrough Data
• PEBL: Positive Example Based Learning for Web Page
• Pattern Discovery in Sequences under a Markov Assumption
• Predicting Rare Classes: Can Boosting Make Any Weak Learner Strong?
• Privacy Preserving Association Rule Mining in Vertically Partitioned Data
• Privacy Preserving Mining of Association Rules
• Query, Analysis, and Visualization of Hierarchically Structured Data using Polaris
• Relational Markov Models and their Application to Adaptive Web Navigation
• S i m R a n k : A M e a s u r e of S t r u c t u r a l - C o n t e x t Similarity*
• SECRET: A Scalable Linear Regression Tree Algorithm
• Scalable Robust Covariance and Correlation Estimates for Data Mining
• Scaling multi-class Support Vector Machines using inter-class confusion
• Selecting the Right Interestingness Measure for Association Patterns
• Sequential Cost-Sensitive Decision Making with Reinforcement Learning
• Sequential PAttern Mining using A Bitmap Representation
• Shrinkage Estimator Generalizations of Proximal Support Vector Machines
• Statistical Modeling of Large-Scale Simulation Data
• SyMP: An Efficient Clustering Approach to Identify Clusters of Arbitrary Shapes in Large Data Sets
• Topics in 0-1 Data
• Transforming Classifier Scores into Accurate Multiclass Probability Estimates
• Transforming Data to Satisfy Privacy Constraints
• Tumor Cell Identification using Features Rules
• Visualization Support for a User-Centered KDD Process
• Web Site Mining : A new way to spot Competitors, Customers and Suppliers in the World Wide Web