Comparison Analysis of Nepali News Classifier

With the growing volume of daily generated Nepali news content, which predominantly exists in unstructured formats, the need arises to effectively categorize and label this information. Considering this challenge, our system employs various Machine Learning algorithms such as Logistic Regression, Random Forest Algorithm, Neural Networks, etc., to automatically classify Nepali news into predefined categories and evaluate the efficiency of the model, which offers us a comparative analysis of these various algorithms.

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Publication Details

Journal
KEC Journal of Science and Engineering
Published
2025-05-07
DOI
https://doi.org/10.3126/kjse.v9i1.78347
Primary Topic
Spam and Phishing Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

Comparison Analysis of Nepali News Classifier

N Shrestha, Kshitiz Shrestha, I Shrestha, Kishor Khanal et al.
KEC Journal of Science and Engineering
Spam and Phishing Detection
article

Comparison Analysis of Nepali News Classifier

N Shrestha, Kshitiz Shrestha, I Shrestha, Kishor Khanal, Kunjan Amatya
article en

Abstract

With the growing volume of daily generated Nepali news content, which predominantly exists in unstructured formats, the need arises to effectively categorize and label this information. Considering this challenge, our system employs various Machine Learning algorithms such as Logistic Regression, Random Forest Algorithm, Neural Networks, etc., to automatically classify Nepali news into predefined categories and evaluate the efficiency of the model, which offers us a comparative analysis of these various algorithms.

KEC Journal of Science and EngineeringVol. 9(1)
Kathmandu College of Management (NP), Kathmandu Medical College Teaching Hospital (NP)
Openalex Percentile: Top 87%
Spam and Phishing Detection
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