Results 201 to 210 of about 29,744 (241)
Some of the next articles are maybe not open access.
Word sense disambiguation for Turkish
2009 24th International Symposium on Computer and Information Sciences, 2009Word Sense Disambiguation (WSD) is the core and one of the hardest problems of many Natural Language Processing tasks. WSD is considered as an AI-complete problem. Although there are many approaches trying to solve this problem, many of them are not adequate to solve WSD problem for Turkish.
Ezgi Mert, Gökhan Dalkiliç
openaire +2 more sources
2013
This chapter discusses the basic concepts of Word Sense Disambiguation (WSD) and the approaches to solving this problem. Both general purpose WSD and domain specific WSD are presented. The first part of the discussion focuses on existing approaches for WSD, including knowledge-based, supervised, semi-supervised, unsupervised, hybrid, and bilingual ...
Pushpak Bhattacharyya, Mitesh Khapra
+5 more sources
This chapter discusses the basic concepts of Word Sense Disambiguation (WSD) and the approaches to solving this problem. Both general purpose WSD and domain specific WSD are presented. The first part of the discussion focuses on existing approaches for WSD, including knowledge-based, supervised, semi-supervised, unsupervised, hybrid, and bilingual ...
Pushpak Bhattacharyya, Mitesh Khapra
+5 more sources
Word sense disambiguation methods
Programming and Computer Software, 2010Word sense disambiguation is one of the key tasks of text processing. It consists in the determination of senses of words or compound terms in accordance with the context where they were used. The word sense disambiguation problem originated in the 1950s as a subtask of machine translation.
openaire +1 more source
Multiwords and Word Sense Disambiguation
2005This paper studies the impact of multiword expressions on Word Sense Disambiguation (WSD). Several identification strategies of the multiwords in WordNet2.0 are tested in a real Senseval-3 task: the disambiguation of WordNet glosses. Although we have focused on Word Sense Disambiguation, the same techniques could be applied in more complex tasks, such ...
Victoria Arranz +2 more
openaire +1 more source
Probabilistic word sense disambiguation
Computer Speech & Language, 2004We present a theoretically motivated method for creating probabilistic word sense disambiguation (WSD) systems. The method works by composing multiple probabilistic components: such modularity is made possible by an application of Bayesian statistics and Lidstone's smoothing method. We show that a probabilistic WSD system created along these lines is a
openaire +1 more source
Smoothing and Word Sense Disambiguation
2004This paper presents an algorithm to apply the smoothing techniques described in [15] to three different Machine Learning (ML) methods for Word Sense Disambiguation (WSD). The method to obtain better estimations for the features is explained step by step, and applied to n-way ambiguities.
Eneko Agirre, David Martínez 0001
openaire +1 more source
Word Sense Disambiguation Based on Word Sense Clustering
2006In this paper we address the problem of Word Sense Disambiguation by introducing a knowledge-driven framework for the disambiguation of nouns. The proposal is based on the clustering of noun sense representations and it serves as a general model that includes some existing disambiguation methods.
Henry Anaya-Sánchez +2 more
openaire +1 more source
Practice of Word Sense Disambiguation
2018The paper aims at the community of researchers and practitioners that work in the area of natural language processing but do not specialize in the word sense disambiguation (WSD). It contains a brief introduction into WSD and describes the classical approaches to solve the problem.
openaire +1 more source
Word Sense Disambiguation with GermaNet
2015The subject of this dissertation is boosting research on word sense disambiguation (WSD) for German. WSD is a very active area of research in computational linguistics, but most of the work is focused on English. One of the factors that has hampered WSD research for other languages such as German is the lack of appropriate resources, particularly in ...
openaire +3 more sources
An improved approach to word sense disambiguation
2014 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT), 2014Words in the English language often correspond to different meanings in different contexts. Such words are referred to as polysemous words i.e. words having more than one sense. This paper presents a knowledge based algorithm for disambiguating polysemous words using computational linguistics tool, WordNet.
Pradeep Sachdeva +2 more
openaire +1 more source