Traditional data mining applications consider the problem of mining a single relation between two attributes. For example, in a scientific bibliography database, authors are rela...
Foto N. Afrati, Gautam Das, Aristides Gionis, Heik...
The objective of this work is to interpret inductive results obtained by the unsupervised learning method OSHAM. We briefly introduce the learning process of OSHAM, that extracts ...
This paper provides algorithms that use an information-theoretic analysis to learn Bayesian network structures from data. Based on our three-phase learning framework, we develop e...
Jie Cheng, Russell Greiner, Jonathan Kelly, David ...
Most data mining algorithms assume static behavior of the incoming data. In the real world, the situation is different and most continuously collected data streams are generated by...
Lior Cohen, Gil Avrahami, Mark Last, Abraham Kande...
Abstract. The web with its rapid expansion has become an excellent resource for gathering information and people’s opinion. A company owner wants to know who is the competitor, a...
Rui Li, Shenghua Bao, Jin Wang, Yuanjie Liu, Yong ...