Web App for Personalized News Recommendation

Author(s)	Mr Aman Gupta, Mr. Jawed Akhtar, Mr Mohd Kaif
Country	India
Abstract	There’s so much information online nowadays that endpoint users often have trouble finding content that is feasible to them. While personalized recommendation systems have come across a long way in areas like e-commerce, advertising, and multimedia , they still have a long way to go before they can be used in E-news. The unique features of digital its size, variety, speedy updates, focus on time, and focus on specific region make it harder to use the current recommendation methods successfully. This paper suggests a multi-modal framework that combines the meaning of language with traits that are not related to language. A robust refining logic is used by the system to focus on real-time voice transcription and voice intensity, which is measured by Root Mean Square (RMS) energy. We test how well the system works by simulating an experiment. The results show that adding acoustic features makes retrieval much more accurate and aligns intent much better than with standard probabilistic models.
Keywords	Root Mean Square, Acoustic
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 8, Issue 3, May-June 2026
Published On	2026-06-16
DOI	https://doi.org/10.36948/ijfmr.2026.v08i03.75592

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