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KDD
2002
ACM
171views Data Mining» more  KDD 2002»
14 years 9 months ago
Mining complex models from arbitrarily large databases in constant time
In this paper we propose a scaling-up method that is applicable to essentially any induction algorithm based on discrete search. The result of applying the method to an algorithm ...
Geoff Hulten, Pedro Domingos
AUSDM
2007
Springer
112views Data Mining» more  AUSDM 2007»
14 years 3 months ago
Measuring Data-Driven Ontology Changes using Text Mining
Most current ontology management systems concentrate on detecting usage-driven changes and representing changes formally in order to maintain the consistency. In this paper, we pr...
Majigsuren Enkhsaikhan, Wilson Wong, Wei Liu, Mark...
WEBI
2004
Springer
14 years 2 months ago
Mining Local Data Sources For Learning Global Cluster Models
— Distributed data mining has recently caught a lot of attention as there are many cases where pooling distributed data for mining is probibited, due to either huge data volume o...
Chak-Man Lam, Xiaofeng Zhang, William Kwok-Wai Che...
WISE
2002
Springer
14 years 2 months ago
Log Mining to Improve the Performance of Site Search
Despite of the popularity of global search engines, people still suffer from low accuracy of site search. The primary reason lies in the difference of link structures and data sca...
Gui-Rong Xue, Hua-Jun Zeng, Zheng Chen, Wei-Ying M...
KDD
2000
ACM
142views Data Mining» more  KDD 2000»
14 years 25 days ago
Automating exploratory data analysis for efficient data mining
Having access to large data sets for the purpose of predictive data mining does not guarantee good models, even when the size of the training data is virtually unlimited. Instead,...
Jonathan D. Becher, Pavel Berkhin, Edmund Freeman