Ethical AI-Powered News Summarization with Core Insights

The rise of digital news makes staying informed challenging. This paper presents an AI-powered news summarization system using NLP and machine learning to extract, analyze, and generate concise, factual summaries. It integrates keyword extraction, sentiment analysis, and ethical evaluation, ensuring unbiased, multi-perspective insights. Leveraging GPT-based models and multi-stage attention mechanisms, the system enhances responsible journalism and information transparency. Key Words: GPT-3, NLP, Multi-Stage Attention Mechanisms, OLLAMA, LLAMA 3.2, Gemini API

Authors

Publication Details

Journal
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Published
2025-03-20
DOI
https://doi.org/10.55041/ijsrem42718
Primary Topic
Topic Modeling
Type
article
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article

Ethical AI-Powered News Summarization with Core Insights

Muthuramalingam Prakash
INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT
Topic Modeling
article

Ethical AI-Powered News Summarization with Core Insights

Muthuramalingam Prakash
article en

Abstract

The rise of digital news makes staying informed challenging. This paper presents an AI-powered news summarization system using NLP and machine learning to extract, analyze, and generate concise, factual summaries. It integrates keyword extraction, sentiment analysis, and ethical evaluation, ensuring unbiased, multi-perspective insights. Leveraging GPT-based models and multi-stage attention mechanisms, the system enhances responsible journalism and information transparency. Key Words: GPT-3, NLP, Multi-Stage Attention Mechanisms, OLLAMA, LLAMA 3.2, Gemini API

INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENTVol. 09(03)
Openalex Percentile: Top 98%
Topic Modeling
DOIOpen Access PDFOpenAlex
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Ethical AI-Powered News Summarization with Core Insights — Muthuramalingam Prakash · INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT (2025) | TGRS Research Map | TGRS