Abstract
Automatic text summarization has very efficient techniques to create the summarization (important information form document) of the text document. As we know the information on the internet is growing rapidly and we cannot go through all the documents on the internet. If we want to read the news we have to identify which news we have to read then the news article can be summarized in only one paragraph by information extraction from the news article and by reading this short paragraph we can identify which article we should read. The automatic text summarization can be done by three methods. First one is the extraction method in which we just find the informative sentences from the whole document text. The second approach is the abstraction technique in which we find the meaning of the sentences and try to formulate the paragraph in the same meaning manner or we can say the same thing express the fewer words. The third and last approach is compression technique in which compress each sentence of the document. We compress the sentence by having the words related to the meaning of the sentence by title or first sentence of the graph. We can apply the hybrid approach to create the summarization in which we first compress the whole text document and then apply knowledge extraction. Knowledge extraction can be done by giving the score to each sentence and then pick the best k sentences according to compression ratio.
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Kharita, M.K., Singh, P. (2020). Automatic Text Summarization Techniques Used in Industry. In: Singh, P., Panigrahi, B., Suryadevara, N., Sharma, S., Singh, A. (eds) Proceedings of ICETIT 2019. Lecture Notes in Electrical Engineering, vol 605. Springer, Cham. https://doi.org/10.1007/978-3-030-30577-2_19
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DOI: https://doi.org/10.1007/978-3-030-30577-2_19
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