Proceedings of the Third SIAM International Conference on Data MiningDaniel Barbara, Chandrika Kamath SIAM, 2003 M01 1 - 347 pages The third SIAM International Conference on Data Mining provided an open forum for the presentation, discussion and development of innovative algorithms, software and theories for data mining applications and data intensive computation. This volume includes 21 research papers. |
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Contents
Feature Mining Paradigms for Scientific Data | 13 |
Fast Online SVD Revisions for Lightweight Recommender Systems | 37 |
Hierarchical Document Clustering Using Frequent Itemsets | 59 |
A New Gravitational Clustering Algorithm | 83 |
Communication and Memory Efficient Parallel Decision Tree Construction | 119 |
Contents | 137 |
Approximate Query Answering by Model Averaging | 142 |
Mining Closed Sequential Patterns in Large Datasets | 166 |
Application to Clustering | 239 |
The Application of Text Mining Software to Examine Coded Information | 254 |
The Analysis of Asthma and Exposure Data Using Geographic Information Systems | 269 |
Learning Bayesian Network Structure from Distributed Data | 284 |
Relationship between Users DB and the Web | 299 |
A Highly Adaptive | 316 |
An OutlierBased Data Association Method for Linking Criminal Incidents | 326 |
Mining Temporal Databases for Subsequence Patterns | 336 |
Anytime QueryTuned Kernel Machines via Cholesky Factorization | 186 |
Toward Computational Tractability | 203 |
On Discovery of Statistically Important Pattern Repeats in Long Sequential Data | 224 |
Common terms and phrases
accuracy analysis applied approach approximation association rules ATLAS attributes AVC groups average BAYESIAN NETWORKS candidate changes clickstream CloSpan clustering algorithm computation Conf constraint contains cooccurrence corresponding data mining data set database decision tree defined density detection dimensionality distance distribution document dynamic edit distance efficient Equation error estimation evaluation example feature selection Figure frequent itemsets function graph information gain input itemsets iteration K-means kd-tree keratoconus Knowledge Discovery Machine Learning matrix memory method min_sup mixture model nearest neighbor node normal number of clusters obtained optimization outliers PageRank paper parameters partition pattern mining performance prediction prefix PrefixSpan problem Proc proposed pruning query random replacement cost sample Satimage score Section sequential pattern SIGKDD similar singular values space StarClass statistical step structure subset Table techniques threshold tion training data tuples update variables vector Zernike polynomial