Harnessing business and media insights with large language models
Published in arXiv preprint arXiv:2406.06559, 2024
This paper presents applications of large language models for extracting actionable insights from business and media data. We demonstrate how LLMs can be leveraged to analyze news articles, financial reports, and social media content to identify trends, sentiments, and emerging topics relevant to business decision-making. Our system provides automated summarization, entity extraction, and relationship mapping capabilities that enable faster and more comprehensive analysis of large document collections.
Recommended citation: @article{bao2024harnessing, title={Harnessing Business and Media Insights with Large Language Models}, author={Bao, Yujia and Shah, Ankit Parag and Narang, Neeru and Rivers, Jonathan and Maksey, Rajeev and Guan, Lan and Barrere, Louise N and Evenson, Shelley and Basole, Rahul and Miao, Connie and others}, journal={arXiv preprint arXiv:2406.06559}, year={2024} }
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