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KDD
2006
ACM
145views Data Mining» more  KDD 2006»
16 years 3 months ago
Deriving quantitative models for correlation clusters
Correlation clustering aims at grouping the data set into correlation clusters such that the objects in the same cluster exhibit a certain density and are all associated to a comm...
Arthur Zimek, Christian Böhm, Elke Achtert, H...
FSTTCS
2009
Springer
15 years 8 months ago
Bounded Size Graph Clustering with Applications to Stream Processing
We introduce a graph clustering problem motivated by a stream processing application. Input to our problem is an undirected graph with vertex and edge weights. A cluster is a subse...
Rohit Khandekar, Kirsten Hildrum, Sujay Parekh, De...
SIGIR
2010
ACM
15 years 3 months ago
Optimal meta search results clustering
By analogy with merging documents rankings, the outputs from multiple search results clustering algorithms can be combined into a single output. In this paper we study the feasibi...
Claudio Carpineto, Giovanni Romano
BMCBI
2011
14 years 10 months ago
A novel approach to the clustering of microarray data via nonparametric density estimation
Background: Cluster analysis is a crucial tool in several biological and medical studies dealing with microarray data. Such studies pose challenging statistical problems due to di...
Riccardo De Bin, Davide Risso
144
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SAC
2002
ACM
15 years 2 months ago
Concurrency control for distributed cooperative engineering applications
Distributed cooperative engineering applications require consistent and long-term sharing of large volumes of data, which may cause conflicts due to concurrent read/write operatio...
João Coelho Garcia, Paulo Ferreira