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» Scaling Clustering Algorithms to Large Databases
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RIAO
2007
13 years 10 months ago
Comprehensible and Accurate Cluster Labels in Text Clustering
The purpose of text clustering in information retrieval is to discover groups of semantically related documents. Accurate and comprehensible cluster descriptions (labels) let the ...
Jerzy Stefanowski, Dawid Weiss
DASFAA
2005
IEEE
137views Database» more  DASFAA 2005»
14 years 2 months ago
A General Approach to Mining Quality Pattern-Based Clusters from Microarray Data
Abstract. Pattern-based clustering has broad applications in microarray data analysis, customer segmentation, e-business data analysis, etc. However, pattern-based clustering often...
Daxin Jiang, Jian Pei, Aidong Zhang
AICT
2007
IEEE
180views Communications» more  AICT 2007»
14 years 2 months ago
BPTraSha: A Novel Algorithm for Shaping Bursty Nature of Internet Traffic
Various researchers have reported that traffic measurements demonstrate considerable burstiness on several time scales, with properties of self-similarity. Also, the rapid developm...
Karim Mohammed Rezaul, Vic Grout
VLDB
1995
ACM
66views Database» more  VLDB 1995»
14 years 1 days ago
A Performance Evaluation of OID Mapping Techniques
In this paper, three techniques to implement logical OIDs are thoroughly evaluated: hashing, B-trees and a technique called direct mapping. Among these three techniques, direct ma...
André Eickler, Carsten Andreas Gerlhof, Don...
EDBT
2000
ACM
14 years 3 days 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...