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IJCNLP
2005
Springer

Mining Inter-Entity Semantic Relations Using Improved Transductive Learning

8 years 10 months ago
Mining Inter-Entity Semantic Relations Using Improved Transductive Learning
This paper studies the problem of mining relational data hidden in natural language text. In particular, it approaches the relation classification problem with the strategy of transductive learning. Different algorithms are presented and empirically evaluated on the ACE corpus. We show that transductive learners exploiting various lexical and syntactic features can achieve promising classification performance. More importantly, transductive learning performance can be significantly improved by using an induced similarity function.
Zhu Zhang
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where IJCNLP
Authors Zhu Zhang
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