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» CURE: An Efficient Clustering Algorithm for Large Databases
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BIODATAMINING
2008
96views more  BIODATAMINING 2008»
15 years 4 months ago
Fast approximate hierarchical clustering using similarity heuristics
Background: Agglomerative hierarchical clustering (AHC) is a common unsupervised data analysis technique used in several biological applications. Standard AHC methods require that...
Meelis Kull, Jaak Vilo
142
Voted
EDBT
2004
ACM
147views Database» more  EDBT 2004»
16 years 4 months ago
Efficient Query Evaluation over Compressed XML Data
XML suffers from the major limitation of high redundancy. Even if compression can be beneficial for XML data, however, once compressed, the data can be seldom browsed and queried i...
Andrei Arion, Angela Bonifati, Gianni Costa, Sandr...
ICDE
2003
IEEE
170views Database» more  ICDE 2003»
16 years 5 months ago
Keyword Proximity Search on XML Graphs
XKeyword provides efficient keyword proximity queries on large XML graph databases. A query is simply a list of keywords and does not require any schema or query language knowledg...
Vagelis Hristidis, Yannis Papakonstantinou, Andrey...
KDD
2004
ACM
147views Data Mining» more  KDD 2004»
15 years 9 months ago
Clustering time series from ARMA models with clipped data
Clustering time series is a problem that has applications in a wide variety of fields, and has recently attracted a large amount of research. In this paper we focus on clustering...
Anthony J. Bagnall, Gareth J. Janacek
DKE
2006
110views more  DKE 2006»
15 years 4 months ago
Efficient mining of group patterns from user movement data
In this paper, we present a new approach to derive groupings of mobile users based on their movement data. We assume that the user movement data are collected by logging location ...
Yida Wang, Ee-Peng Lim, San-Yih Hwang