Using Exponential Kernel for Word Sense Disambiguation

2013 ◽  
pp. 545-552 ◽  
Author(s):  
Tinghua Wang ◽  
Junyang Rao ◽  
Dongyan Zhao
Keyword(s):  
Word Sense Disambiguation ◽  
Word Sense ◽  
Exponential Kernel ◽  
Sense Disambiguation

Using Exponential Kernel for Semi-Supervised Word Sense Disambiguation

2016 ◽  
Vol 13 (10) ◽  
pp. 6929-6934
Author(s):  
Junting Chen ◽  
Liyun Zhong ◽  
Caiyun Cai
Keyword(s):  
Natural Language ◽  
Language Processing ◽  
Word Sense Disambiguation ◽  
Training Data ◽  
Support Vector ◽  
Svm Classifier ◽  
Data Sets ◽  
Word Sense ◽  
Exponential Kernel ◽  
Sense Disambiguation

Word sense disambiguation (WSD) in natural language text is a fundamental semantic understanding task at the lexical level in natural language processing (NLP) applications. Kernel methods such as support vector machine (SVM) have been successfully applied to WSD. This is mainly due to their relatively high classification accuracy as well as their ability to handle high dimensional and sparse data. A significant challenge in WSD is to reduce the need for labeled training data while maintaining an acceptable performance. In this paper, we present a semi-supervised technique using the exponential kernel for WSD. Specifically, the semantic similarities between terms are first determined with both labeled and unlabeled training data by means of a diffusion process on a graph defined by lexicon and co-occurrence information, and the exponential kernel is then constructed based on the learned semantic similarity. Finally, the SVM classifier trains a model for each class during the training phase and this model is then applied to all test examples in the test phase. The main feature of this approach is that it takes advantage of the exponential kernel to reveal the semantic similarities between terms in an unsupervised manner, which provides a kernel framework for semi-supervised learning. Experiments on several SENSEVAL benchmark data sets demonstrate the proposed approach is sound and effective.

Graph Based Word Sense Disambiguation Method Using Distance Between Words

2012 ◽  
Vol 23 (4) ◽  
pp. 776-785 ◽  
Author(s):  
Zhi-Zhuo YANG ◽  
He-Yan HUANG
Keyword(s):  
Word Sense Disambiguation ◽  
Word Sense ◽  
Sense Disambiguation

scholarly journals Multimodal Word Sense Disambiguation in Creative Practice

2020 ◽  
Author(s):  
Manuel Ladron de Guevara ◽  
Christopher George ◽  
Akshat Gupta ◽  
Daragh Byrne ◽  
Ramesh Krishnamurti
Keyword(s):  
Word Sense Disambiguation ◽  
Word Sense ◽  
Creative Practice ◽  
Sense Disambiguation

scholarly journals Spreading semantic information by Word Sense Disambiguation

2017 ◽  
Vol 132 ◽  
pp. 47-61 ◽  
Author(s):  
Yoan Gutiérrez ◽  
Sonia Vázquez ◽  
Andrés Montoyo
Keyword(s):  
Semantic Information ◽  
Word Sense Disambiguation ◽  
Word Sense ◽  
Sense Disambiguation

Word Sense Disambiguation in the Biomedical Domain: An Overview

2005 ◽  
Vol 12 (5) ◽  
pp. 554-565 ◽  
Author(s):  
Martijn J. Schuemie ◽  
Jan A. Kors ◽  
Barend Mons
Keyword(s):  
Word Sense Disambiguation ◽  
Biomedical Domain ◽  
Word Sense ◽  
Sense Disambiguation
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