Comparison of Algorithms in Authorship Identification using Bengali Poems

  • Authors

    • A. Pandian
    • V. Ramalingam
    • K. Manikandan
    • Payal Bhowmick
    • Shree Vaishnavi
    2018-11-27
    https://doi.org/10.14419/ijet.v7i4.19.21989
  • Authorship identification, Bengali poems, J48 decision tree.

  • Abstract

    Author identification of Bengali poems is a paper mainly focusing on identification of an author of a poem. We train the system using a dataset consisting of features extracted from poems by various authors. Features like count of characters, words, spaces, vowels and consonants of Bengali poems are considered. Many training algorithms can be used to identify the authors. Some of the algorithms are J48, SVM, PCA, RDM, Random Forest Tree, Logic Regression, Naive Bayes etc. Every algorithm has its own advantages and disadvantages. The training algorithm used the most is J48 decision tree. It has additional features such as accounting for missing values, decision trees pruning, continuous attribute value ranges, derivation of rules, etc. which will be helpful when we want to classify with larger datasets.

     

  • References

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  • How to Cite

    Pandian, A., Ramalingam, V., Manikandan, K., Bhowmick, P., & Vaishnavi, S. (2018). Comparison of Algorithms in Authorship Identification using Bengali Poems. International Journal of Engineering & Technology, 7(4.19), 22-25. https://doi.org/10.14419/ijet.v7i4.19.21989

    Received date: 2018-11-28

    Accepted date: 2018-11-28

    Published date: 2018-11-27