13 search results - page 1 / 3 » A Seed-driven Bottom-up Machine Learning Framework for Extra... |
ACL
2007
13 years 6 months ago
2007
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...
IS
2008
13 years 4 months ago
2008
This paper approaches the relation classification problem in information extraction framework with different machine learning strategies, from strictly supervised to weakly superv...
ICDM
2008
IEEE
13 years 11 months ago
2008
IEEE
Supervised approaches to Data Mining are particularly appealing as they allow for the extraction of complex relations from data objects. In order to facilitate their application i...
COLT
2000
Springer
13 years 8 months ago
2000
Springer
The present paper deals with the averagecase complexity of various algorithms for learning univariate polynomials. For this purpose an appropriate framework is introduced. Based o...
PR
2010
13 years 2 months ago
2010
Selecting relevant features for Support Vector Machine (SVM) classifiers is important for a variety of reasons such as generalization performance, computational efficiency, and ...