Abstract Word Sense Disambiguation (WSD) is significant for improving the accuracy of the
interpretation of a Natural language text. Various supervised learning-based models and …

Abstract The problem of Word Sense Disambiguation (WSD) can be defined as the task of
assigning the most appropriate sense to the polysemous word within a given context. Many …

Hindi language is written and spoken by majority of people in India. Like other natural
languages, Hindi is also an ambiguous language which creates obstacle in usage of …

The purpose of this study is to facilitate knowledge discovery about the relationship between
driving and health among the elderly. In the Iwaki Health Promotion Project that is an annual …

Abstract In this work, Word Sense Disambiguation (WSD) in Bengali language is
implemented using unsupervised methodology. In the first phase of this experiment …

Word Sense Disambiguation (WSD) is a vital task which provides the definition of particular
words according to their sense or according to given context. Lesk algorithm is originally …

In this paper, we have implemented a novel unsupervised graph-based algorithm for Hindi
Word Sense Disambiguation. For disambiguation, we perform a random walk on graph …

There has been a recent boom in research relating semantic space computational models to
fMRI data, in an effort to better understand how the brain represents semantic information. In …

One of the central challenging and most difficult problems in Natural Language Processing
is the capability to identify what a word means with respect to a context in which it comes into …

Hindi is the regional language of India. Most of the people access, retrieve, and share
documents in Hindi language. As all the natural languages possess property of being …