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EUROPAR
1999
Springer
15 years 2 months ago
Parallel k/h-Means Clustering for Large Data Sets
This paper describes the realization of a parallel version of the k/h-means clustering algorithm. This is one of the basic algorithms used in a wide range of data mining tasks. We ...
Kilian Stoffel, Abdelkader Belkoniene
IPPS
2008
IEEE
15 years 4 months ago
Parallel mining of closed quasi-cliques
Graph structure can model the relationships among a set of objects. Mining quasi-clique patterns from large dense graph data makes sense with respect to both statistic and applica...
Yuzhou Zhang, Jianyong Wang, Zhiping Zeng, Lizhu Z...
DMIN
2006
141views Data Mining» more  DMIN 2006»
14 years 11 months ago
Detecting Cheats In Online Student Assessments Using Data Mining
: We can find several online assessment applications, Windows oriented or Web based, licensed or gnu free software, proprietary or standardized. All of them executing basic questio...
Genadiy Burlak, Jaime Muñoz, Alberto Ochoa,...
IPPS
2009
IEEE
15 years 4 months ago
Multi-dimensional characterization of temporal data mining on graphics processors
Through the algorthmic design patterns of data parallelism and task parallelism, the graphics processing unit (GPU) offers the potential to vastly accelerate discovery and innovat...
Jeremy S. Archuleta, Yong Cao, Thomas Scogland, Wu...
GFKL
2005
Springer
93views Data Mining» more  GFKL 2005»
15 years 3 months ago
A Hybrid Machine Learning Approach for Information Extraction from Free Text
Abstract. We present a hybrid machine learning approach for information extraction from unstructured documents by integrating a learned classifier based on the Maximum Entropy Mod...
Günter Neumann