Text Summarizing of vast information using Graphical User Interface

Authors

  • Hemanth Kumar B. UG Scholar, Saveetha School of Engineering, Saveetha Institute of Medical and TechnicalSciences, Chennai, India Author
  • Dr.L.Ramaparvathy Assistant Professor, Saveetha School of Engineering, Saveetha Institute of Medical and Technical,Sciences, Chennai, India Author

DOI:

https://doi.org/10.61841/nbpqkm66

Keywords:

Natural Language Processing, NLTK library

Abstract

Text summarization is one of those employments of natural language processing (NLP) that will, in fact, have an extraordinary impact on our lives. For the most part, text outline can completely be separated into two requests, extractive summarization and abstractive summarization, and the execution of the seq2seq model for the outline of academic information utilizing tensor stream/keras showed up on Amazon or social reaction surveys, issues, and reports. Content outline is a subdomain of natural language processing that administers removing rundowns from immense bits of work. There are two key sorts of strategies utilized for content outline: NLP-based systems and noteworthy learning-based techniques. In this way, our point is to look at spacy, gensim, and NLTK summary structure by the data basics. It will see a fundamental NLP-based system for content synopsis. Or then again, perhaps it will basically utilize Python's NLTK library for content gathering. 

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References

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Published

30.04.2020

Issue

Vol. 24 No. 2 (2020): 24 (2) 2020

Section

Articles

License

Copyright (c) 2020 AUTHOR

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How to Cite

B., H. K., & L., R. (2020). Text Summarizing of vast information using Graphical User Interface. International Journal of Psychosocial Rehabilitation, 24(2), 4591-4599. https://doi.org/10.61841/nbpqkm66