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» Performance prediction for set similarity joins
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PVLDB
2010
126views more  PVLDB 2010»
13 years 3 months ago
Set Similarity Join on Probabilistic Data
Set similarity join has played an important role in many real-world applications such as data cleaning, near duplication detection, data integration, and so on. In these applicati...
Xiang Lian, Lei Chen 0002
DEXA
2003
Springer
193views Database» more  DEXA 2003»
13 years 9 months ago
Supporting KDD Applications by the k-Nearest Neighbor Join
Abstract. The similarity join has become an important database primitive to support similarity search and data mining. A similarity join combines two sets of complex objects such t...
Christian Böhm, Florian Krebs
KDD
2001
ACM
253views Data Mining» more  KDD 2001»
14 years 5 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
ASYNC
1998
IEEE
91views Hardware» more  ASYNC 1998»
13 years 8 months ago
Predicting Performance of Micropipelines Using Charlie Diagrams
A technique is presented to predict the performance behavior of control circuits for a linear FIFO. The control circuit consists of a linear chain of RendezVous elements, also cal...
Jo C. Ebergen, Scott Fairbanks, Ivan E. Sutherland
GIS
2006
ACM
14 years 5 months ago
Query optimizer for spatial join operations
This paper presents a query optimizer module based on cost estimation that chooses the best filtering step algorithm to perform a specific spatial join operation. A set of express...
Cirano Iochpe, João Luiz Dihl Comba, Miguel...