Adapted Lesk Algorithm based Word Sense Disambiguation using the Context Information

The process of identifying the meaning of a polysemous word correctly from a given context is known as the Word Sense Disambiguation (WSD) in natural language processing (NLP). Adapted Lesk algorithm based system is proposed which makes use of knowledge based approach. This work utilizes WordNet as the knowledge source (lexical database). The proposed system has three units – Input query, Pre-Processing and WSD classifier. Task of input query is to take the inputs sentence (which is an unstructured query) from the user and render it to the pre-processing unit. Pre-processing unit will convert the received unstructured query into a structured query by adding some features such as Part of Speech (POS) tagging, grammatical identification (Subject, Verb, and Object) and this structured query is transferred to the WSD classifier. WSD classifier uniquely identifies the sense of the polysemous word using the context information of the query and the lexical database.

@article{Kumar2020,
  title     = {Adapted Lesk Algorithm based Word Sense Disambiguation using the Context Information},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {11},
  number    = {3},
  year      = {2020},
  publisher = {The Science and Information Organization},
  author    = {Manish Kumar and Prasenjit Mukherjee and Manik Hendre and Manish Godse and Baisakhi Chakraborty},
  doi       = {10.14569/IJACSA.2020.0110330},
  url       = {https://doi.org/10.14569/IJACSA.2020.0110330}
}