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» Efficient Set Similarity Joins Using Min-prefixes
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BCB
2010
126views Bioinformatics» more  BCB 2010»
13 years 2 months ago
Functional similarities of reaction sets in metabolic pathways
Analyzing metabolic pathways by means of their steady states has proven to be accurate and efficient for practical purposes. The models such as elementary flux modes (EFMs) and ex...
Ferhat Ay, Tamer Kahveci
VLDB
2005
ACM
112views Database» more  VLDB 2005»
14 years 28 days ago
REED: Robust, Efficient Filtering and Event Detection in Sensor Networks
This paper presents a set of algorithms for efficiently evaluating join queries over static data tables in sensor networks. We describe and evaluate three algorithms that take adv...
Daniel J. Abadi, Samuel Madden, Wolfgang Lindner
CVPR
2008
IEEE
13 years 7 months ago
A similarity measure between unordered vector sets with application to image categorization
We present a novel approach to compute the similarity between two unordered variable-sized vector sets. To solve this problem, several authors have proposed to model each vector s...
Yan Liu, Florent Perronnin
DEXA
2006
Springer
151views Database» more  DEXA 2006»
13 years 9 months ago
An Incremental Refining Spatial Join Algorithm for Estimating Query Results in GIS
Geographic information systems (GIS) must support large georeferenced data sets. Due to the size of these data sets finding exact answers to spatial queries can be very time consum...
Wan D. Bae, Shayma Alkobaisi, Scott T. Leutenegger
KDD
2001
ACM
253views Data Mining» more  KDD 2001»
14 years 7 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