Abstract
For many decades researchers in the domain of NLP (Natural Language Processing) and its applications like Machine Translation, Text Mining, Question Answering, Information Extraction and Information retrieval etc. have been posed with a challenging area of research i.e. WSD (Word Sense Disambiguation) WSD can be defined as the ability to correctly ascertain the meaning of a word, with reference to the context in which the word was used. Linguistics, has defined context as the passage, sentence or text in which the word appears that is used for ascertaining its meaning. Thus, context is dependent on the POS (Part Of Speech) where the word is used e.g. Adverb, Adjective, Pronoun, Verb and Noun. In the following study we recommend a unique way of WSD based on Context through WordNet, multimodal algorithm that is knowledge based, map-reduce and soft sense WSD.
Cite
CITATION STYLE
Hamid, S., K.A., S., & Hasan, F. (2015). Word Sense Disambiguation – A Context based Multimode WSD Model. International Journal of Computer Applications, 126(8), 34–37. https://doi.org/10.5120/ijca2015906174
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