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» MapReduce: Simplified Data Processing on Large Clusters
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WSDM
2012
ACM
329views Data Mining» more  WSDM 2012»
12 years 4 months ago
Beyond 100 million entities: large-scale blocking-based resolution for heterogeneous data
A prerequisite for leveraging the vast amount of data available on the Web is Entity Resolution, i.e., the process of identifying and linking data that describe the same real-worl...
George Papadakis, Ekaterini Ioannou, Claudia Niede...
CEC
2005
IEEE
14 years 2 months ago
Multiobjective clustering around medoids
Abstract- The large majority of existing clustering algorithms are centered around the notion of a feature, that is, individual data items are represented by their intrinsic proper...
Julia Handl, Joshua D. Knowles
MM
2009
ACM
125views Multimedia» more  MM 2009»
14 years 3 months ago
Unfolding speaker clustering potential: a biomimetic approach
Speaker clustering is the task of grouping a set of speech utterances into speaker-specific classes. The basic techniques for solving this task are similar to those used for spea...
Thilo Stadelmann, Bernd Freisleben
SBACPAD
2003
IEEE
180views Hardware» more  SBACPAD 2003»
14 years 2 months ago
New Parallel Algorithms for Frequent Itemset Mining in Very Large Databases
Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in finding frequent patterns (or itemsets) hidden in large volumes of d...
Adriano Veloso, Wagner Meira Jr., Srinivasan Parth...
SDM
2008
SIAM
256views Data Mining» more  SDM 2008»
13 years 10 months ago
Graph Mining with Variational Dirichlet Process Mixture Models
Graph data such as chemical compounds and XML documents are getting more common in many application domains. A main difficulty of graph data processing lies in the intrinsic high ...
Koji Tsuda, Kenichi Kurihara