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» Composite Kernels For Relation Extraction
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SKG
2006
IEEE
14 years 7 days ago
Embedding the Semantic Knowledge in Convolution Kernels
Convolution kernels, such as tree kernel and subsequence kernel are useful for natural language processing tasks. However, most of them ignore the semantic knowledge. In order to ...
Kebin Liu, Fang Li, Ying Han, Lei Liu
EUSFLAT
2009
132views Fuzzy Logic» more  EUSFLAT 2009»
13 years 4 months ago
Modeling Position Specificity in Sequence Kernels by Fuzzy Equivalence Relations
This paper demonstrates that several known sequence kernels can be expressed in a unified framework in which the position specificity is modeled by fuzzy equivalence relations. In ...
Ulrich Bodenhofer, Karin Schwarzbauer, Mihaela Ion...
ACL
2007
13 years 7 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
ISCAPDCS
2003
13 years 7 months ago
Using Kernel Coupling to Improve the Performance of Multithreaded Applications
Kernel coupling refers to the effect that kernel i has on kernel j in relation to running each kernel in isolation. The two kernels can correspond to adjacent kernels or a chain ...
Jonathan Geisler, Valerie E. Taylor, Xingfu Wu, Ri...
COLING
2010
13 years 1 months ago
Exploiting Background Knowledge for Relation Extraction
Relation extraction is the task of recognizing semantic relations among entities. Given a particular sentence supervised approaches to Relation Extraction employed feature or kern...
Yee Seng Chan, Dan Roth