Now days, Word Sense Disambiguation (WSD) is a vital area which is very useful in today’s world. Many WSD algorithms are available in literature; we have chosen to an optimal and portable WSD algorithm. We are discussed the supervised, unsupervised, and knowledge-based approaches for WSD. In this paper we are discuses that association rules, Knowledge-based WSD, Corpus-based WSD.

In the field of natural language processing, semantic disambiguation words is beneficial to several applications, which helps us identify correct meaning a word or sequence according given context. It can be formulated as combinatorial optimization problem where goal find set meanings that contribute improving relationship between target words. The Crow Search Algorithm (CSA) nature-inspired al...

White Spot Disease (WSD) is well known as a widespread viral disease in shrimps from 1992. Many studies focused on morphological, histopathological and epidemiological characteristic and pathogenecity of the disease but less on the determination of the severity of WSD using the histopathological features in target tissues. A generalized scheme for assigning a numerical qualitative value to sev...

While much effort has been put in designing and evaluating Word Sense Disambiguation (WSD) models for translation in the WSD community, standard Statistical Machine Translation (SMT) systems have achieved remarkable improvements in translation quality without modeling WSD explicitly. However, inspecting SMT output suggests that SMT needs better semantic modeling to accurately translate meaning....

Word Sense Disambiguation (WSD) is an important but challenging technique in the area of natural language processing (NLP). Hundreds of WSD algorithms and systems are available, but less work has been done in regard to choosing the optimal WSD algorithms. This paper summarizes the various knowledge sources used for WSD and classifies existing WSD algorithms according to their techniques. The ra...

Word Sense Disambiguation (WSD) is a significant and challenging task for text understanding processing. This paper presents an unsupervised approach based on Weighted Co-occurrence bio-Term Graph (WCOTG) performing WSD in the biomedical domain. The graph automatically created from terms that are extracted corpus of downloaded scientific abstracts. Two kinds weights introduced links built bio-t...

Resumen: Este artículo describe el impacto de un algoritmo de Desambiguación de Sentidos de Palabras (WSD) para nombres en AliQAn, el sistema de Question Answering con el cual hemos participado en el CLEF-2005. Al aplicar el WSD tradicional, el rendimiento se decrementa en un 4.7% en el Mean Reciprocal Rank (MRR). Para resolver este problema, proponemos dos aplicaciones de WSD: (1) elegir un gr...

Word sense disambiguation (WSD) is the problem of deciding which sense a word has in any given context. The problem of doing WSD by computer is not new; it goes back to the early days of machine translation. But like other areas of computational linguistics, research into WSD has seen a resurgence because of the availability of large corpora. Statistical methods for WSD, especially techniques i...