Assessing Policy Effectiveness using AI and Language Models: Applications for Economic and Social Sustainability...

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Chandrasekar Vuppalapati

Assessing Policy Effectiveness using AI and Language Models

Applications for Economic and Social Sustainability

Chandrasekar Vuppalapati

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English

Springer International Publishing AG
31 May 2024

Political economy; Management decision making; Operational research; Artificial intelligence; Machine learning

Series: International Series in Operations Research & Management Science

This volume uses advanced machine learning techniques to analyze government communication to evaluate policy effectiveness. The book develops policy effectiveness foundation models by cohorting historical budget policies with statistical models which are built on well reputed data sources including economic events, macroeconomic trends, and ratings and commerce terms from international institutions. By signal mining policies to the economic outcome patterns, the book aims to create a rich source of successful policy insights in terms of their effectiveness in bringing development to the poor and underserved communities to ensure the spread of wealth, social wellbeing, and standard of living to the common denomination of society rather than a selected quotient. Enabling academics and practitioners across disciplines to develop applications for effective policy interventions, this volume will be of interest to a wide audience including software engineers, data scientists, social scientists, economists, and agriculture practitioners.

By: Chandrasekar Vuppalapati
Imprint: Springer International Publishing AG
Country of Publication: Switzerland
Edition: 2024 ed.
Volume: 354
Dimensions: Height: 235mm, Width: 155mm,
ISBN: 9783031560965
ISBN 10: 3031560965
Series: International Series in Operations Research & Management Science
Pages: 467
Publication Date: 31 May 2024
Audience: Professional and scholarly , Undergraduate
Format: Hardback
Publisher's Status: Active

Chandrasekar Vuppalapati is a seasoned Software IT Executive with diverse experience in software technologies, enterprise software architectures, cloud computing, big data business analytics, internet of things (IoT), and software product and program management. He has held engineering and product leadership positions at Microsoft, GE Healthcare, Cisco Systems, St. Jude Medical, and Lucent Technologies. Chandrasekar has an MS in software engineering from San Jose State University (USA) and an MBA from Santa Clara University (USA) and currently teaches software engineering, large-scale analytics, data science, mobile computing, cloud technologies, and web and data mining at San Jose State University (USA).