Finding author similarity by clustering probabilistic LSA factors in INDIAN english authors poetry

  • Authors

    • K Praveen kumar
    • Venkata Naresh Mandhala
    • Sudheshna Vempati
    • Dr Subba Rao Peram
    2018-03-18
    https://doi.org/10.14419/ijet.v7i2.7.12235
  • LSA, PLSA, Word Occurrence, High Dimensionality

  • Abstract

    High dimensionality and sparseness is the big challenge to the data scientists to discover the similarity among the documents. In unsuper-vised learning data is unlabeled and there is no clear distance measures to discover the clusters among the data. In this paper we considered Indian English Authors poems to cluster them using Probabilistic Latent Semantic Analysis, using which we analyzed the authors similarity. We compared the results of clustering with Latent Semantic Analysis method, a word occurrence method. In this case, Results are shown that probabilistic methods are performing good clustering than the word occurrence method.

     

     

  • References

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      [8] K. Praveenkumar., T. M. Padmaja, “An Analysis on Computational Approach for Finding Similarity in Indian English Authors Poetryâ€, International Conference on SMART DSC-2017, Vignan Institute of Information Technology, Visakhapatnam, on November 30 to December 02, 2017, Advanced Science and Technology Letters,Vol.147 (SMART DSC-2017), pp. 193–203, 2017.

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  • How to Cite

    Praveen kumar, K., Naresh Mandhala, V., Vempati, S., & Subba Rao Peram, D. (2018). Finding author similarity by clustering probabilistic LSA factors in INDIAN english authors poetry. International Journal of Engineering & Technology, 7(2.7), 1096-1099. https://doi.org/10.14419/ijet.v7i2.7.12235

    Received date: 2018-04-27

    Accepted date: 2018-04-27

    Published date: 2018-03-18