Multi Document Text Summarization

Computer Engineering

Summarization process is always needs more precision and time to yield the best results. This is due to the vastness of the data, complexities in the narration of the documents and constrained time boundaries. So the task of Document summary extraction is always full of complexities. So this is the key point in many sections of society where work is lagging behind like court rooms, Academic carrier and many more due to unavailability of the document summary on time. Natural language processing and Machine learning always plays a vital role in providing the summary of the documents, but accuracy is always a big question. So this research article concentrates on extraction of the semantic Summary for the input of multiple documents. This paper introduces using of the Gaussian distribution model and Fuzzy classification along with the natural language processing technique to yield well semantic summary for the given input of the multi documents.

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