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Ihr LexisNexis-Team

Assessing Policy Effectiveness using AI and Language Models

Applications for Economic and Social Sustainability
ISBN:
978-3-03-156099-6
Verlag:
Springer International Publishing
Land des Verlags:
Schweiz
Erscheinungsdatum:
31.05.2025
Reihe:
International Series in Operations Research & Management Science
Format:
Softcover
Seitenanzahl:
467
Ladenpreis
164,99EUR (inkl. MwSt. zzgl. Versand)
Lieferung in 5-10 Werktagen Versandkostenfrei ab 40 Euro in Österreich
Hinweis: Da dieses Werk nicht aus Österreich stammt, ist es wahrscheinlich, dass es nicht die österreichische Rechtslage enthält. Bitte berücksichtigen Sie dies bei ihrem Kauf.

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.

Biografische Anmerkung

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).