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» CURE: An Efficient Clustering Algorithm for Large Databases
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KDD
2004
ACM
145views Data Mining» more  KDD 2004»
16 years 4 months ago
Mining coherent gene clusters from gene-sample-time microarray data
Extensive studies have shown that mining microarray data sets is important in bioinformatics research and biomedical applications. In this paper, we explore a novel type of genesa...
Daxin Jiang, Jian Pei, Murali Ramanathan, Chun Tan...
SAC
2008
ACM
15 years 3 months ago
Adding background knowledge to formal concept analysis via attribute dependency formulas
We present a way to add user's background knowledge to formal concept analysis. The type of background knowledge we deal with relates to relative importance of attributes in ...
Radim Belohlávek, Vilém Vychodil
BALT
2006
15 years 7 months ago
Introducing Softness into Inductive Queries on String Databases
In many application domains (e.g., WWW mining, molecular biology), large string datasets are available and yet under-exploited. The inductive database framework assumes that both s...
Ieva Mitasiunaite, Jean-François Boulicaut
PKDD
2004
Springer
277views Data Mining» more  PKDD 2004»
15 years 9 months ago
Scalable Density-Based Distributed Clustering
Clustering has become an increasingly important task in analysing huge amounts of data. Traditional applications require that all data has to be located at the site where it is scr...
Eshref Januzaj, Hans-Peter Kriegel, Martin Pfeifle
168
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ICRA
2009
IEEE
218views Robotics» more  ICRA 2009»
15 years 1 months ago
Automatically and efficiently inferring the hierarchical structure of visual maps
In Simultaneous Localisation and Mapping (SLAM), it is well known that probabilistic filtering approaches which aim to estimate the robot and map state sequentially suffer from poo...
Margarita Chli, Andrew J. Davison