PAKDD 2004 - PDF Preprint Papers

PAKDD 2004 Pacific-Asia Conference on Knowledge Discovery and Data Mining

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PAKDD
2004
ACM

199views Data Mining» more PAKDD 2004»

Temporal Sequence Associations for Rare Events

13 years 9 months ago

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In many real world applications, systematic analysis of rare events, such as credit card frauds and adverse drug reactions, is very important. Their low occurrence rate in large da...

Jie Chen, Hongxing He, Graham J. Williams, Huidong...

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Id	Views	Title	Status

1	199	Temporal Sequence Associations for Rare Events	claim
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3	183	Constraint-Based Graph Clustering through Node Sequencing and Partitioning	claim
4	164	FP-Bonsai: The Art of Growing and Pruning Small FP-Trees	claim
5	159	Summarization of Spacecraft Telemetry Data by Extracting Significant Temporal Patterns	claim
6	143	Compact Dual Ensembles for Active Learning	claim
7	137	Fast and Light Boosting for Adaptive Mining of Data Streams	claim
8	131	Mining of Web-Page Visiting Patterns with Continuous-Time Markov Models	claim
9	131	A Tree-Based Approach to the Discovery of Diagnostic Biomarkers for Ovarian Cancer	claim
10	127	Separating Structure from Interestingness	claim
11	127	Exploiting Recurring Usage Patterns to Enhance Filesystem and Memory Subsystem Performance	claim
12	121	Secure Association Rule Sharing	claim
13	119	Mining Negative Rules Using GRD	claim
14	117	Constraint-Based Mining of Formal Concepts in Transactional Data	claim
15	113	Logistic Regression and Boosting for Labeled Bags of Instances	claim
16	108	A Metric Approach to Building Decision Trees Based on Goodman-Kruskal Association Index	claim
17	105	Extracting and Explaining Biological Knowledge in Microarray Data	claim
18	100	Using Self-Consistent Naive-Bayes to Detect Masquerades	claim
19	97	Further Applications of a Particle Visualization Framework	claim
20	96	Spectral Energy Minimization for Semi-supervised Learning	claim
21	94	Self-Similar Mining of Time Association Rules	claim
22	94	Towards Optimizing Conjunctive Inductive Queries	claim
23	94	Clustering Multi-represented Objects with Noise	claim
24	83	Providing Diversity in K-Nearest Neighbor Query Results	claim

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