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» Shallow Semantic Parsing using Support Vector Machines
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COLING
2008
13 years 7 months ago
A Hybrid Generative/Discriminative Framework to Train a Semantic Parser from an Un-annotated Corpus
We propose a hybrid generative/discriminative framework for semantic parsing which combines the hidden vector state (HVS) model and the hidden Markov support vector machines (HMSV...
Deyu Zhou, Yulan He
ECML
2006
Springer
13 years 9 months ago
Efficient Convolution Kernels for Dependency and Constituent Syntactic Trees
In this paper, we provide a study on the use of tree kernels to encode syntactic parsing information in natural language learning. In particular, we propose a new convolution kerne...
Alessandro Moschitti
COLING
2010
13 years 15 days ago
Shallow Information Extraction from Medical Forum Data
We study a novel shallow information extraction problem that involves extracting sentences of a given set of topic categories from medical forum data. Given a corpus of medical fo...
Parikshit Sondhi, Manish Gupta, ChengXiang Zhai, J...
IJCNN
2000
IEEE
13 years 10 months ago
Support Vector Machines Based on a Semantic Kernel for Text Categorization
We propose to solve a text categorization task using a new metric between documents, based on a priori semantic knowledge about words. This metric can be incorporated into the def...
George Siolas, Florence d'Alché-Buc
ACL
2006
13 years 7 months ago
Discriminative Classifiers for Deterministic Dependency Parsing
Deterministic parsing guided by treebankinduced classifiers has emerged as a simple and efficient alternative to more complex models for data-driven parsing. We present a systemat...
Johan Hall, Joakim Nivre, Jens Nilsson