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Compression Based Modeling for Classification of Text Documents

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Recent Trends in Image Processing and Pattern Recognition (RTIP2R 2018)

Abstract

Classification of text data one of the well known, interesting research topic in computer science and knowledge engineering. This research article, address the classification of text files issue using lzw text compression algorithms. LZW is a lossless compression technique which requires two pass on the input data. These two passes are treated separately as training stage and text stage for classification of text data. The proposed compression based classification technique is tested on publically available datasets. Results of the experiments shows the effectiveness of the proposed algorithm.

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Correspondence to S. N. Bharath Bhushan .

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Bhushan, S.N.B., Danti, A. (2019). Compression Based Modeling for Classification of Text Documents. In: Santosh, K., Hegadi, R. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2018. Communications in Computer and Information Science, vol 1037. Springer, Singapore. https://doi.org/10.1007/978-981-13-9187-3_63

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  • DOI: https://doi.org/10.1007/978-981-13-9187-3_63

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-9186-6

  • Online ISBN: 978-981-13-9187-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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