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SDM
2009
SIAM
251views Data Mining» more  SDM 2009»
14 years 7 months ago
High Performance Parallel/Distributed Biclustering Using Barycenter Heuristic.
Biclustering refers to simultaneous clustering of objects and their features. Use of biclustering is gaining momentum in areas such as text mining, gene expression analysis and co...
Alok N. Choudhary, Arifa Nisar, Waseem Ahmad, Wei-...
ICDCS
2006
IEEE
14 years 3 months ago
ParRescue: Scalable Parallel Algorithm and Implementation for Biclustering over Large Distributed Datasets
Biclustering refers to simultaneously capturing correlations present among subsets of attributes (columns) and records (rows). It is widely used in data mining applications includ...
Jianhong Zhou, Ashfaq A. Khokhar
ECAI
2010
Springer
13 years 11 months ago
Learning Aggregation Functions for Expert Search
Abstract. Machine learning techniques are increasingly being applied to problems in the domain of information retrieval and text mining. In this paper we present an application of ...
Ronan Cummins, Mounia Lalmas, Colm O'Riordan
WWW
2009
ACM
14 years 10 months ago
Searching for events in the blogosphere
Over the last few years, blogs (web logs) have gained massive popularity and have become one of the most influential web social media in our times. Every blog post in the Blogosph...
Manolis Platakis, Dimitrios Kotsakos, Dimitrios Gu...
SDM
2003
SIAM
184views Data Mining» more  SDM 2003»
13 years 11 months ago
Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data
The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
Levent Ertöz, Michael Steinbach, Vipin Kumar