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Paper Title
Evaluation of Python Text Summarization Libraries
  Tripti Sharma,  Anmol Ashri,  Navin Kumar,  Shubham Pal,  Rajat

Text summarization is a process of condensing the source data into a concise version of text while preserving important information content and overall meaning. In this study we have analysed the accuracies of summaries provided by the NLTK,spaCy,Gensim,Sumy and compare those summaries with original summary provided by the dataset as reference summaries in order to calculate the BLEU score for the assessment of the summaries provided by these python libraries. Dataset used, is taken from kaggle.com, dataset contains 4515 different examples with original summaries of each example. All the results and experimentation made using Python 3 in Jupyter Notebook.

Keywords- Text Summarization,NLTK,spaCy,Gensim,Sumy,BLEU
Publication Details
Unique Identification Number - IJEDR2101019
Page Number(s) - 159-164
Pubished in - Volume 9 | Issue 1 | January 2021
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
  Tripti Sharma,  Anmol Ashri,  Navin Kumar,  Shubham Pal,  Rajat,   "Evaluation of Python Text Summarization Libraries", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.9, Issue 1, pp.159-164, January 2021, Available at :http://www.ijedr.org/papers/IJEDR2101019.pdf
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