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» Shallow Semantic Parsing using Support Vector Machines
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COLING
2008
15 years 1 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
115
Voted
ECML
2006
Springer
15 years 3 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
14 years 6 months 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
15 years 4 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
15 years 29 days 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