In a world that routinely produces more textual data. It is very critical task to managing that textual data. There are many text analysis methods are available to managing and visualizing that data, but many techniques may give less accuracy because of the ambiguity of natural language. To provide the ne grained analysis, in this paper introduce e cient machine learning algorithms for categorize text data. To improve the accuracy, in proposed system I introduced Natural language toolkit NLTK python library to perform natural language processing. The main aim of proposed system is to generalize the model for real time text categorization applications by using e cient text classi cation as well as clustering machine learning algorithms and nd the efficient and accurate model for input dataset using performance measure concept.
Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019,
URL: https://www.ijtsrd.com/papers/ijtsrd25077.pdf
Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/25077/experimental-result-analysis-of-text-categorization-using-clustering-and-classification-algorithms/patil-kiran-sanajy
international journals in engineering, international journal of management, international journal of science
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