Paper Title
Telugu News Classification
Article Identifiers
Registration ID: IJNRD_214995
Published ID: IJNRD2403119
: http://doi.one/10.1729/Journal.38232
Authors
Keywords
Text classification, Telugu text classification, Heap’s law, tokenization, stop words, n-gram model, punctuation
Abstract
The rapid progress in the field of IT has resulted in the accumulation of a vast volume of textual files. While researchers have predominantly focused on English text files in the past, there is now a substantial amount of content available in various Indian regional languages. Presently, there is a continuous generation of digitized Telugu text documents from government websites, news portals, and both public and private sectors on a daily basis. It is crucial to efficiently categorize these documents into predefined classes for easy retrieval. Text classification, a branch of Text Mining, offers a viable solution to this challenge. Text classification involves the automated categorization of these documents, which is otherwise a labor-intensive and time-consuming task when done manually. Automating this classification process can greatly enhance document management and retrieval. In this research paper, we present the results obtained through the application of methodologies such as Heap's law and n-gram models.
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How To Cite (APA)
S.Rohit Jaiswal, Geeda Dilip Reddy, Kodhati Sidharth Rao, Durbhakula Haranath, & Dr. Subhranginee Das (March-2024). Telugu News Classification. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(3), b192-b197. http://doi.one/10.1729/Journal.38232
Issue
Volume 9 Issue 3, March-2024
Pages : b192-b197
Other Publication Details
Paper Reg. ID: IJNRD_214995
Published Paper Id: IJNRD2403119
Downloads: 000122025
Research Area: Engineering
Author Type: Indian Author
Country: Hyderabad, Telangana, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2403119.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2403119
Crossref DOI: http://doi.one/10.1729/Journal.38232
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