Publication | Closed Access
Extractive Automatic Text Summarization using SpaCy in Python & NLP
56
Citations
7
References
2021
Year
EngineeringEntity SummarizationNarrative SummarizationCorpus LinguisticsText MiningAutomatic SummarizationNatural Language ProcessingInformation RetrievalData ScienceText SummarizationComputational LinguisticsLanguage StudiesContent AnalysisMachine TranslationCoherent SummaryKnowledge DiscoveryComputer ScienceInformation ExtractionAutomatic Text SummarizationMulti-modal SummarizationText ProcessingLinguistics
Propulsion of the everchanging technological innovations, has led to consider the data generated in the present era very crucial with significant roles both in technical & nontechnical fields. In the digital world, as the amount of data produced at every instance is very huge; there is an ultimate need to develop a machine that can reduce the length of the texts automatically. Moreover, applying text summarization gears up the procedure of researching, reduces reading time, and increases the amount of important information being generated in the specific field. The main agenda is to develop a meaningful and coherent summary to recapitulate highlights of the text. From the collection of fascinating problems, we have opted for the Automatic Text Summarization. The solution to this problem unlike doing manually has proved to be essential in accurately summarizing voluminous texts in a cost and time efficient manner.
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