Model for Classification of Poems in Hindi Language Based on Ras

  • Kaushika PalEmail author
  • Biraj V. Patel
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 141)


The developed model will classify poem into Shringar, Hasya, Adbhuta, Shanta, Raudra, Veera, Karuna, Bhayanaka, Vibhasta rasas, which will use mix of part-of-speech-based feature and emotional features to classify the poem. Emotional features are features, which are responsible for particular emotion and it is represented in 9 categories. We have 9 classes each class-containing feature for one class, overlapping of feature is possible and is dealt with term frequency in the document. The classifiers used are support vector machine and naive Bayes. The model has used 55 poems as a dataset of all 9 genres consisting of 10531 words.


Machine learning Feature selection Classification NLP Ras 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Sarvajanik College of Engineering and TechnologySuratIndia
  2. 2.G.H. Patel, P.G. Department of Computer Science and TechnologySardar Patel UniversityAnandIndia

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