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A Survey on Word Sense Disambiguation for Persian language

Suliman Ameryani, Nirav M Raja, Vishal Prajapati

Abstract


Natural language processing (NLP) is considered as one of the most important subfields of Artificial Intelligence. It’s used to provide an Interface between Computer and Human languages. NLP has found its application on several areas such as Speech processing, Summation of text, Machine translation, Searching, Information grouping, Parts of Speech Tagging (POS), Sentiment analysis and etc. Natural language processing is posing some challenges in speech recognition, ambiguity in preposition attachment, co-reference resolution, Information extraction, question answering, word sense disambiguation (WSD) and etc. Many algorithms have been proposed so far to address the mentioned problems in NLP and some techniques for WSD too. Word sense disambiguation (WSD) is the process of finding correct sense for a word from a collection of semantic tags (senses) in a sentence. It has application in Machine translation, Information retrieval, Information extraction and Knowledge acquisition. Along with the other languages like English, Spanish, French, Hindi that are the focus point for most of the researchers some work has been done for Persian language too. This paper aims to describe some aspect of NLP and approaches that applied on WSD for Persian Language with analysis.

Keywords


Natural language processing, word sense disambiguation, Ambiguity, Persian language

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References


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