DATAMINE 2006 - PDF Preprint Papers

DATAMINE 2006

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DATAMINE
2006

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Mining top-K frequent itemsets from data streams

14 years 14 days ago

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Frequent pattern mining on data streams is of interest recently. However, it is not easy for users to determine a proper frequency threshold. It is more reasonable to ask users to ...

Raymond Chi-Wing Wong, Ada Wai-Chee Fu

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Id	Views	Title	Status

1	230	Mining top-K frequent itemsets from data streams	claim
2	224	Characteristic-Based Clustering for Time Series Data	claim
3	176	A Bit Level Representation for Time Series Data Mining with Shape Based Similarity	claim
4	166	Accelerated EM-based clustering of large data sets	claim
5	164	Fast Distributed Outlier Detection in Mixed-Attribute Data Sets	claim
6	157	Data Clustering with Partial Supervision	claim
7	142	Sequential Pattern Mining in Multi-Databases via Multiple Alignment	claim
8	139	Discovering Classification from Data of Multiple Sources	claim
9	139	VizRank: Data Visualization Guided by Machine Learning	claim
10	131	A systematic approach to the assessment of fuzzy association rules	claim
11	130	Mining Adaptive Ratio Rules from Distributed Data Sources	claim
12	127	Computing LTS Regression for Large Data Sets	claim
13	117	A Rule-Based Approach for Process Discovery: Dealing with Noise and Imbalance in Process Logs	claim
14	97	Reinforcing Web-object Categorization Through Interrelationships	claim
15	89	Scalable Clustering Algorithms with Balancing Constraints	claim
16	88	Hyperclique pattern discovery	claim
17	83	Structural Hidden Markov Models Using a Relation of Equivalence: Application to Automotive Designs	claim
18	80	Mining in Anticipation for Concept Change: Proactive-Reactive Prediction in Data Streams	claim
19	79	Mining Multiple Data Sources: Local Pattern Analysis	claim

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