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.
CITATION STYLE
Pal, K., & Patel, B. V. (2020). Model for Classification of Poems in Hindi Language Based on Ras. In Smart Innovation, Systems and Technologies (Vol. 141, pp. 655–661). Springer. https://doi.org/10.1007/978-981-13-8406-6_62
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