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» CURE: An Efficient Clustering Algorithm for Large Databases
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134
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EDBT
2000
ACM
15 years 7 months ago
Mining Classification Rules from Datasets with Large Number of Many-Valued Attributes
Decision tree induction algorithms scale well to large datasets for their univariate and divide-and-conquer approach. However, they may fail in discovering effective knowledge when...
Giovanni Giuffrida, Wesley W. Chu, Dominique M. Ha...
157
Voted
ICPPW
2009
IEEE
15 years 1 months ago
A Scalable Parallel Approach for Peptide Identification from Large-Scale Mass Spectrometry Data
Identifying peptides, which are short polymeric chains of amino acid residues in a protein sequence, is of fundamental importance in systems biology research. The most popular appr...
Gaurav Ramesh Kulkarni, Ananth Kalyanaraman, Willi...
122
Voted
ICPADS
2005
IEEE
15 years 9 months ago
An Efficient Partition-Based Parallel PageRank Algorithm
PageRank becomes the most well-known re-ranking technique of the search results. By its iterative computational nature, the computation takes much computing time and resource. Res...
Bundit Manaskasemsak, Arnon Rungsawang
134
Voted
ICIP
2001
IEEE
16 years 5 months ago
Video similarity detection with video signature clustering
The proliferation of video content on the web makes similarity detection an indispensable tool in web data management, searching, and navigation. We have previously proposed a com...
Sen-Ching S. Cheung, Avideh Zakhor
275
Voted
PADL
2009
Springer
16 years 4 months ago
Using Bloom Filters for Large Scale Gene Sequence Analysis in Haskell
Analysis of biological data often involves large data sets and computationally expensive algorithms. Databases of biological data continue to grow, leading to an increasing demand ...
Ketil Malde, Bryan O'Sullivan