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» Clustering Improves the Exploration of Graph Mining Results
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SIGKDD
2000
95views more  SIGKDD 2000»
14 years 11 months ago
Scalability for Clustering Algorithms Revisited
This paper presents a simple new algorithm that performs k-means clustering in one scan of a dataset, while using a bu er for points from the dataset of xed size. Experiments show...
Fredrik Farnstrom, James Lewis, Charles Elkan
GECCO
2009
Springer
199views Optimization» more  GECCO 2009»
15 years 4 months ago
Using behavioral exploration objectives to solve deceptive problems in neuro-evolution
Encouraging exploration, typically by preserving the diversity within the population, is one of the most common method to improve the behavior of evolutionary algorithms with dece...
Jean-Baptiste Mouret, Stéphane Doncieux
CIKM
2009
Springer
15 years 6 months ago
Networks, communities and kronecker products
Emergence of the web and online computing applications gave rise to rich large scale social activity data. One of the principal challenges then is to build models and understandin...
Jure Leskovec
IPM
2007
145views more  IPM 2007»
14 years 11 months ago
Text mining techniques for patent analysis
Patent documents contain important research results. However, they are lengthy and rich in technical terminology such that it takes a lot of human efforts for analyses. Automatic...
Yuen-Hsien Tseng, Chi-Jen Lin, Yu-I Lin
ICDM
2002
IEEE
163views Data Mining» more  ICDM 2002»
15 years 4 months ago
High Performance Data Mining Using the Nearest Neighbor Join
The similarity join has become an important database primitive to support similarity search and data mining. A similarity join combines two sets of complex objects such that the r...
Christian Böhm, Florian Krebs