Bi-Channel Generative Recurrent Network-Based Identification of Marathi Poems - Saxena, Vineet; Singh, Vikram; Bhatt, Chetan; Ojha, Ananta Charan (International Journal of Intelligent Systems and Applications in Engineering, 2023)
The term "Marathi poems" refers to writings in the Marathi language, which is largely used in the Indian state of Maharashtra and certain surrounding areas. With contributions from notable poets over the ages, Marathi poetry has a rich legacy and a lengthy history. It is used to display various perspectives. Every poet has a particular purpose and point of view when we classifies the poem. A recurrent network that recognizes Marathi poetry may be trained using a dataset of Marathi poems, where each poem is represented as a collection of words or characters. The poem was categorized in the suggested way utilizing terms from several categories by its thoughts. The poem's classification is determined using the machine learning method Bi-Channel Generative Recurrent Network (BI-CGRN) classifier. Additionally, this method allows users to search for poems depending on the name and category of author. The recommended technique surpasses earlier approaches for 336 poems, increasing the BI-CGRN classification's accuracy. To evaluate the performance of the suggested approach, the dataset is used. The noisy data are taken out of the samples of raw data using the Adaptive Median Filter (AMF). The properties are extracted using a Kernel Principal Component Analysis (KPCA). The results of the research demonstrate that accuracy, precision, f1-score, and recall measures to illustrate the performance of poetry for five categories, including "Friend," "Prem," "Bhakti," "Prerna," and "Desh," are important. The recommended method makes it easier to identify and categorize Marathi poetry, which may help to preserve and promote Marathi literary history.