Translation Disambiguation Based on 'Word-to-Sense and Sense-to-Word' Relationship

Word Sense Disambiguation Based on Word Sense Clustering

Word Sense Disambiguation Based Myanmar-to-english Machine Translation System

Today, word sense disambiguation (WSD) is an important technique for many natural language processing (NLP) applications such as grammatical analysis, content analysis, information retrieval and machine translation. Among them, the WSD technique is used for machine translation to find the correct sense of a word in a specific context. In machine translation, the input sentences in the source la...

Approaches To Word Sense Disambiguation

Removing ambiguous meaning of a word has been an extensive area of research in the field of computational linguistics. This paper presents a comprehensive study of the different dictionary approaches to Word Sense Disambiguation. Three approaches have been explored; graph based, ontology based and knowledge based. All the approaches use a corpus to evaluate words unlike in a machine learning ap...

Concept-Based Approach to Word-Sense Disambiguation

The task of automatically determining the correct sense of a polysemous word has remained a challenge to this day. In our research, we introduce Concept-Based Disambiguation (CBD), a novel framework that utilizes recent semantic analysis techniques to represent both the context of the word and its senses in a high-dimensional space of natural concepts. The concepts are retrieved from a vast enc...

I2R: Three Systems for Word Sense Discrimination, Chinese Word Sense Disambiguation, and English Word Sense Disambiguation

This paper describes the implementation of our three systems at SemEval-2007, for task 2 (word sense discrimination), task 5 (Chinese word sense disambiguation), and the first subtask in task 17 (English word sense disambiguation). For task 2, we applied a cluster validation method to estimate the number of senses of a target word in untagged data, and then grouped the instances of this target ...