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COLING
2000
15 years 6 months ago
Structural Feature Selection For English-Korean Statistical Machine Translation
When aligning texts in very different languages such as Korean and English, structural features beyond word or phrase give useful intbrmation. In this paper, we present a method f...
Seonho Kim, Juntae Yoon, Mansuk Song
IJCAI
1997
15 years 6 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
NAACL
1994
15 years 6 months ago
Building Japanese-English Dictionary based on Ontology for Machine Translation
This paper describes a semi-automatic method for associating a Japanese lexicon with a semantic concept taxonomy called an ontology, using a Japanese-English bilingual dictionary ...
Akitoshi Okumura, Eduard H. Hovy
132
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CORR
2006
Springer
143views Education» more  CORR 2006»
15 years 5 months ago
Revealing the Autonomous System Taxonomy: The Machine Learning Approach
Although the Internet AS-level topology has been extensively studied over the past few years, little is known about the details of the AS taxonomy. An AS "node" can repre...
Xenofontas A. Dimitropoulos, Dmitri V. Krioukov, G...
TNN
2008
97views more  TNN 2008»
15 years 5 months ago
Training Hard-Margin Support Vector Machines Using Greedy Stagewise Algorithm
Hard-margin support vector machines (HM-SVMs) suffer from getting overfitting in the presence of noise. Soft-margin SVMs deal with this problem by introducing a regularization term...
Liefeng Bo, Ling Wang, Licheng Jiao