Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
In today’s fast-growing information age we have an abundance of text, especially on the web. New information is continuously being generated. The growing accessibility of online information has necessitated intensive research in the area of automatic text summarization within the Natural Language Processing (NLP) community. Often due to time constraints we are not able to consume all the data available. It is therefore essential to be able to summarize the text so that it becomes easier to ingest, while maintaining the essence and understandability of the information. In this paper we aim to design an algorithm that can summarize a input document by extracting action word and attempting to modify this extraction using a NLP tools. Our main goal is to reduce a given body of text to a fraction of its size, maintaining coherence and semantics of original text and it is Multi-lingual system.
"Literature Review on Optimizing Accuracy of Document Summarization", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.2, Issue 6, page no.111 - 115, June-2017, Available :http://www.ijrti.org/papers/IJRTI1706023.pdf
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator