SIGKDD(KDD) 1997 论文列表
Proceedings of the Third International Conference on Knowledge Discovery and Data Mining (KDD-97), Newport Beach, California, USA, August 14-17, 1997.
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From Large to Huge: A Statistician's Reactions to KDD & DM.
A Dataset Decomposition Approach to Data Mining and Machine Discovery.
Optimal Multiple Intervals Discretization of Continuous Attributes for Supervised Learning.
KDD Process Planning.
Fast and Intuitive Clustering of Web Documents.
New Algorithms for Fast Discovery of Association Rules.
Knowledge Discovery in Integrated Call Centers: A Framework for Effective Customer-Driven Marketing.
Selecting Features by Vertical Compactness of Data.
Schema Discovery for Semistructured Data.
Bayesian Inference for Identifying Solar Active Regions.
An Efficient Algorithm for the Incremental Updation of Association Rules in Large Databases.
Autonomous Discovery of Reliable Exception Rules.
Image Feature Reduction through Spoiling: Its Application to Multiple Matched Filters for Focus of Attention.
Learning to Extract Text-Based Information from the World Wide Web.
KESO: Minimizing Database Interaction.
Visualizing Bagged Decision Trees.
Scaling Up Inductive Algorithms: An Overview.
Beyond Concise and Colorful: Learning Intelligible Rules.
Fast Robust Visual Data Mining.
Discovering Trends in Text Databases.
Mining for Causes of Cancer: Machine Learning Experiments at Various Levels of Detail.
A Unified Notion of Outliers: Properties and Computation.
Clustering Sequences of Complex Objects.
Scalable, Distributed Data Mining - An Agent Architecture.
Metarule-Guided Mining of Multi-Dimensional Association Rules Using Data Cubes.
Mining Generalized Term Associations: Count Propagation Algorithm.
SIPping from the Data Firehose.
Adjusting for Multiple Comparisons in Decision Tree Pruning.
Zeta: A Global Method for Discretization of Continuous Variables.
Target-Independent Mining for Scientific Data: Capturing Transients and Trends for Phenomena Mining.
GA-Based Rule Enhancement in Concept Learning.
Integrating and Mining Distributed Customer Databases.
Deep Knowledge Discovery from Natural Language Texts.
Improving Scalability in a Scientific Discovery System by Exploiting Parallelism.
Maximal Association Rules: A New Tool for Mining for Keyword Co-Occurrences in Document Collections.
A Guided Tour through the Data Mining Jungle.
Fast Committee Machines for Regression and Classification.
Why Does Bagging Work? A Bayesian Account and its Implications.
Mining Multivariate Time-Series Sensor Data to Discover Behavior Envelopes.
Using Artificial Intelligence Planning to Automate Science Data Analysis for Large Image Databases.
Large Scale Data Mining: Challenges and Responses.
Proposal and Empirical Comparison of a Parallelizable Distance-Based Discretization Method.
MineSet: An Integrated System for Data Mining.
Process-Based Database Support for the Early Indicator Method.
Applying Data Mining and Machine Learning Techniques to Submarine Intelligence Analysis.
Brute-Force Mining of High-Confidence Classification Rules.
Increasing the Efficiency of Data Mining Algorithms with Breadth-First Marker Propagation.
Partial Classification Using Association Rules.
Discovery of Actionable Patterns in Databases: The Action Hierarchy Approach.
Knowledge = Concepts: A Harmful Equation.
Computing Optimized Rectilinear Regions for Association Rules.
Automated Discovery of Active Motifs in Three Dimensional Molecules.
A Visual Interactive Framework for Attribute Discretization.
JAM: Java Agents for Meta-Learning over Distributed Databases.
Mining Association Rules with Item Constraints.
Detecting Atmospheric Regimes Using Cross-Validated Clustering.
Anytime Exploratory Data Analysis for Massive Data Sets.
Discriminative vs Informative Learning.
Analysis and Visualization of Classifier Performance: Comparison under Imprecise Class and Cost Distributions.
Development of Multi-Criteria Metrics for Evaluation of Data Mining Algorithms.
Using General Impressions to Analyze Discovered Classification Rules.
A Probabilistic Approach to Fast Pattern Matching in Time Series Databases.
Visualization Techniques to Explore Data Mining Results for Document Collections.
Density-Connected Sets and their Application for Trend Detection in Spatial Databases.
An Interactive Visualization Environment for Data Exploration.
