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» On Kernel Methods for Relational Learning
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COLING
2002
15 years 3 months ago
Extracting Word Sequence Correspondences with Support Vector Machines
This paper proposes a learning and extracting method of word sequence correspondences from non-aligned parallel corpora with Support Vector Machines, which have high ability of th...
Kengo Sato, Hiroaki Saito
ICML
2005
IEEE
16 years 4 months ago
Combining model-based and instance-based learning for first order regression
T ORDER REGRESSION (EXTENDED ABSTRACT) Kurt Driessensa Saso Dzeroskib a Department of Computer Science, University of Waikato, Hamilton, New Zealand (kurtd@waikato.ac.nz) b Departm...
Kurt Driessens, Saso Dzeroski
ML
2008
ACM
15 years 3 months ago
Margin-based first-order rule learning
Abstract We present a new margin-based approach to first-order rule learning. The approach addresses many of the prominent challenges in first-order rule learning, such as the comp...
Ulrich Rückert, Stefan Kramer
EMNLP
2010
15 years 1 months ago
A Semi-Supervised Approach to Improve Classification of Infrequent Discourse Relations Using Feature Vector Extension
Several recent discourse parsers have employed fully-supervised machine learning approaches. These methods require human annotators to beforehand create an extensive training corp...
Hugo Hernault, Danushka Bollegala, Mitsuru Ishizuk...
PRICAI
2000
Springer
15 years 7 months ago
A Comparative Study on Chinese Text Categorization Methods
Abstract. This paper reports our comparative evaluation of three machine learning methods on Chinese text categorization. Whereas a wide range of methods have been applied to Engli...
Ji He, Ah-Hwee Tan, Chew Lim Tan