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» Techniques of Cluster Algorithms in Data Mining
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ICDM
2007
IEEE
137views Data Mining» more  ICDM 2007»
16 years 20 days ago
Locally Constrained Support Vector Clustering
Support vector clustering transforms the data into a high dimensional feature space, where a decision function is computed. In the original space, the function outlines the bounda...
Dragomir Yankov, Eamonn J. Keogh, Kin Fai Kan
DKE
2002
218views more  DKE 2002»
15 years 6 months ago
Computing iceberg concept lattices with T
We introduce the notion of iceberg concept lattices and show their use in knowledge discovery in databases. Iceberg lattices are a conceptual clustering method, which is well suit...
Gerd Stumme, Rafik Taouil, Yves Bastide, Nicolas P...
SBACPAD
2003
IEEE
180views Hardware» more  SBACPAD 2003»
15 years 11 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...
WSDM
2012
ACM
329views Data Mining» more  WSDM 2012»
14 years 1 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...
ICDM
2005
IEEE
188views Data Mining» more  ICDM 2005»
15 years 12 months ago
CLUMP: A Scalable and Robust Framework for Structure Discovery
We introduce a robust and efficient framework called CLUMP (CLustering Using Multiple Prototypes) for unsupervised discovery of structure in data. CLUMP relies on finding multip...
Kunal Punera, Joydeep Ghosh