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» Efficient join processing over uncertain data
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KAIS
2008
150views more  KAIS 2008»
14 years 9 months ago
A survey on algorithms for mining frequent itemsets over data streams
The increasing prominence of data streams arising in a wide range of advanced applications such as fraud detection and trend learning has led to the study of online mining of freq...
James Cheng, Yiping Ke, Wilfred Ng
SIGMOD
2009
ACM
190views Database» more  SIGMOD 2009»
15 years 10 months ago
Optimizing complex extraction programs over evolving text data
Most information extraction (IE) approaches have considered only static text corpora, over which we apply IE only once. Many real-world text corpora however are dynamic. They evol...
Fei Chen 0002, Byron J. Gao, AnHai Doan, Jun Yang ...
SIGMOD
2006
ACM
194views Database» more  SIGMOD 2006»
15 years 10 months ago
Graph-based synopses for relational selectivity estimation
This paper introduces the Tuple Graph (TuG) synopses, a new class of data summaries that enable accurate selectivity estimates for complex relational queries. The proposed summari...
Joshua Spiegel, Neoklis Polyzotis
ICDE
2009
IEEE
174views Database» more  ICDE 2009»
15 years 4 months ago
Sketching Sampled Data Streams
—Sampling is used as a universal method to reduce the running time of computations – the computation is performed on a much smaller sample and then the result is scaled to comp...
Florin Rusu, Alin Dobra
KDD
2001
ACM
253views Data Mining» more  KDD 2001»
15 years 10 months ago
GESS: a scalable similarity-join algorithm for mining large data sets in high dimensional spaces
The similarity join is an important operation for mining high-dimensional feature spaces. Given two data sets, the similarity join computes all tuples (x, y) that are within a dis...
Jens-Peter Dittrich, Bernhard Seeger