Comparative Study Analysis on News Articles Categorization using LSA and NMF Approaches
- Title
- Comparative Study Analysis on News Articles Categorization using LSA and NMF Approaches
- Creator
- Rupendra Reddy B.; Sai Tharun Reddy D.; Sandeep Preetham M.C.; Rajasekhar A.H.N.; Subramani R.
- Description
- Due to exponentially growing news articles every day, most of their important data goes unnoticed. It is important to come up with the ability to automatically analyse these articles and segregate them based on the context and related to their particular domain. This paper applies topic modelling which is one of the most growing unsupervised machine learning fields on a million headlines articles in order to produce topics to describe the context of the news article. There are various generative models but we specifically focusing on the non-negative matrix factorization (NMF) and Latent Semantic Analysis (LSA) for implementing and evaluating news dataset. Furthermore, the findings reveal that both NMF and LSA are useful topic modelling tools and classification frameworks, but based on the experimental results the LSA model performed well to identify the hidden data with better mean coherence values and also consumes lesser execution time than NMF. 2022 IEEE.
- Source
- 2022 13th International Conference on Computing Communication and Networking Technologies, ICCCNT 2022
- Date
- 2022-01-01
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Subject
- LSA; News articles; NMF; Topic modelling
- Coverage
- Rupendra Reddy B., Amrita School of Computing, Department of Computer Science and Engineering, Amrita Vishwa Vidyapeetham, Bengaluru, India; Sai Tharun Reddy D., Amrita School of Computing, Department of Computer Science and Engineering, Amrita Vishwa Vidyapeetham, Bengaluru, India; Sandeep Preetham M.C., Amrita School of Computing, Department of Computer Science and Engineering, Amrita Vishwa Vidyapeetham, Bengaluru, India; Rajasekhar A.H.N., Amrita School of Computing, Department of Computer Science and Engineering, Amrita Vishwa Vidyapeetham, Bengaluru, India; Subramani R., Department of Mathematics, CHRIST (Deemed to Be University), Bengaluru, 560029, India
- Rights
- Restricted Access
- Relation
- ISBN: 978-166545262-5
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Rupendra Reddy B.; Sai Tharun Reddy D.; Sandeep Preetham M.C.; Rajasekhar A.H.N.; Subramani R., “Comparative Study Analysis on News Articles Categorization using LSA and NMF Approaches,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/20195.