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ACL
2007
15 years 5 months ago
A Seed-driven Bottom-up Machine Learning Framework for Extracting Relations of Various Complexity
A minimally supervised machine learning framework is described for extracting relations of various complexity. Bootstrapping starts from a small set of n-ary relation instances as...
Feiyu Xu, Hans Uszkoreit, Hong Li
ECML
2006
Springer
15 years 7 months ago
Why Is Rule Learning Optimistic and How to Correct It
Abstract. In their search through a huge space of possible hypotheses, rule induction algorithms compare estimations of qualities of a large number of rules to find the one that ap...
Martin Mozina, Janez Demsar, Jure Zabkar, Ivan Bra...
ICDM
2009
IEEE
207views Data Mining» more  ICDM 2009»
15 years 1 months ago
Spatially Adaptive Classification and Active Learning of Multispectral Data with Gaussian Processes
Multispectral remote sensing images are widely used for automated land use and land cover classification tasks. Remotely sensed images usually cover large geographical areas, and s...
Goo Jun, Ranga Raju Vatsavai, Joydeep Ghosh
LCN
2005
IEEE
15 years 9 months ago
Automated Traffic Classification and Application Identification using Machine Learning
The dynamic classification and identification of network applications responsible for network traffic flows offers substantial benefits to a number of key areas in IP network engi...
Sebastian Zander, Thuy T. T. Nguyen, Grenville J. ...
IJCAI
1997
15 years 5 months ago
Machine Learning Techniques to Make Computers Easier to Use
Identifying user-dependent information that can be automatically collected helps build a user model by which 1) to predict what the user wants to do next and 2) to do relevant pre...
Hiroshi Motoda, Kenichi Yoshida