Abstract

This paper discuss various technique of word sense disambiguation. In WSD we disambiguate the correct sense of target word present in the text. WSD is a challenging field in the natural language processing, it helps in information retrieval, information extraction, machine learning. There are two approaches for WSD machine learning approach and knowledge based approach. In Knowledge based approach a external resource is used to help in disambiguation process, but in Machine learning approach a corpus is used whether it is annotated, un-annotated or both.

Highlights

  • Almost in all human languages there are words, which have different own separate sense in different context

  • Word sense disambiguation is important machine Tranlation(ML), Semantic mapping(SM), ontology Learning(OL), Semantic Annotation(SA), it helps in Information Retrieval(IR), Information Extraction(IE)

  • We the human being are with intelligence, we can get the proper sense of the polysemous word in particular context

Read more

Summary

INTRODUCTION

Almost in all human languages there are words, which have different own separate sense in different context. This is a important approach in natural language processing(NLP). We the human being are with intelligence, we can get the proper sense of the polysemous word in particular context. We can do it with the help of surrounding words i.e. the local or global context. After the system can disambiguate the proper sense of the ambiguous word in the particular context. With the machine learning we can only process the sentence and if any polysemous word occurs the surrounding of the ambiguous context of the target word is analyzed.

DICTONARY BASE APPROACH
Lesk Algorithm
Selection Preferences
MACHINE LEARNING APPROACH
Supervised Word Sense Disambiguation
Unsupervised Machine Learning Approach
Semi-Supervised Machine Learning Approach
CONCLUSION
REFRENCES

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.