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ICDM
2007
IEEE
158views Data Mining» more  ICDM 2007»
14 years 2 months ago
On Appropriate Assumptions to Mine Data Streams: Analysis and Practice
Recent years have witnessed an increasing number of studies in stream mining, which aim at building an accurate model for continuously arriving data. Somehow most existing work ma...
Jing Gao, Wei Fan, Jiawei Han
DAWAK
2010
Springer
13 years 8 months ago
Mining Closed Itemsets in Data Stream Using Formal Concept Analysis
Mining of frequent closed itemsets has been shown to be more efficient than mining frequent itemsets for generating non-redundant association rules. The task is challenging in data...
Anamika Gupta, Vasudha Bhatnagar, Naveen Kumar
KDD
2010
ACM
300views Data Mining» more  KDD 2010»
13 years 11 months ago
Mining top-k frequent items in a data stream with flexible sliding windows
We study the problem of finding the k most frequent items in a stream of items for the recently proposed max-frequency measure. Based on the properties of an item, the maxfrequen...
Hoang Thanh Lam, Toon Calders
DAWAK
2006
Springer
13 years 11 months ago
An Approximate Approach for Mining Recently Frequent Itemsets from Data Streams
Recently, the data stream, which is an unbounded sequence of data elements generated at a rapid rate, provides a dynamic environment for collecting data sources. It is likely that ...
Jia-Ling Koh, Shu-Ning Shin
ASC
2008
13 years 7 months ago
Info-fuzzy algorithms for mining dynamic data streams
Most data mining algorithms assume static behavior of the incoming data. In the real world, the situation is different and most continuously collected data streams are generated by...
Lior Cohen, Gil Avrahami, Mark Last, Abraham Kande...