Zero-shot word sense disambiguation using sense definition embeddings
Abstract Word Sense Disambiguation (WSD) is a long-standing but open problem in Natural
Language Processing (NLP). WSD corpora are typically small in size, owing to an expensive …
Language Processing (NLP). WSD corpora are typically small in size, owing to an expensive …
Knowledge-based word sense disambiguation using topic models
Abstract Word Sense Disambiguation is an open problem in Natural Language Processing
which is particularly challenging and useful in the unsupervised setting where all the words …
which is particularly challenging and useful in the unsupervised setting where all the words …
A game-theoretic approach to word sense disambiguation
This article presents a new model for word sense disambiguation formulated in terms of
evolutionary game theory, where each word to be disambiguated is represented as a node …
evolutionary game theory, where each word to be disambiguated is represented as a node …
Word sense disambiguation based on context selection using knowledge-based word similarity
In this paper, we introduce a novel knowledge-based word-sense disambiguation (WSD)
system. In particular, the main goal of our research is to find an effective way to filter out …
system. In particular, the main goal of our research is to find an effective way to filter out …
Entity linking: an issue to extract corresponding entity with knowledge base
G Wu, Y He, X Hu - IEEE Access, 2018 - ieeexplore.ieee.org
Entity linking is a task to extract query mentions in documents, and then link them to their
corresponding entities in a knowledge base. It can improve the performances of knowledge …
corresponding entities in a knowledge base. It can improve the performances of knowledge …
Word sense disambiguation based on word similarity calculation using word vector representation from a knowledge-based graph
Word sense disambiguation (WSD) is the task to determine the word sense according to its
context. Many existing WSD studies have been using an external knowledge-based …
context. Many existing WSD studies have been using an external knowledge-based …
Try to substitute: An unsupervised chinese word sense disambiguation method based on hownet
Word sense disambiguation (WSD) is a fundamental natural language processing task.
Unsupervised knowledge-based WSD only relies on a lexical knowledge base as the sense …
Unsupervised knowledge-based WSD only relies on a lexical knowledge base as the sense …
Neural machine translation with Gumbel Tree-LSTM based encoder
Neural machine translation has improved the translation accuracy greatly and received
great attention of the machine translation community. Tree-based translation models aim to …
great attention of the machine translation community. Tree-based translation models aim to …
Optimal high-order tensor svd via tensor-train orthogonal iteration
This paper studies a general framework for high-order tensor SVD. We propose a new
computationally efficient algorithm, tensor-train orthogonal iteration (TTOI), that aims to …
computationally efficient algorithm, tensor-train orthogonal iteration (TTOI), that aims to …
[HTML][HTML] An unsupervised method for word sense disambiguation
Word sense disambiguation (WSD) finds the actual meaning of a word according to its
context. This paper presents a novel WSD method to find the correct sense of a word present …
context. This paper presents a novel WSD method to find the correct sense of a word present …