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Record Nr. |
UNINA9910865258603321 |
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Autore |
Vuppalapati Chandrasekar <1972-> |
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Titolo |
Assessing Policy Effectiveness using AI and Language Models : Applications for Economic and Social Sustainability / / by Chandrasekar Vuppalapati |
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Pubbl/distr/stampa |
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
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ISBN |
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9783031560972 |
9783031560965 |
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Edizione |
[1st ed. 2024.] |
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Descrizione fisica |
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1 online resource (481 pages) |
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Collana |
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International Series in Operations Research & Management Science, , 2214-7934 ; ; 354 |
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Disciplina |
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Soggetti |
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Operations research |
Economic policy |
Social policy |
Machine learning |
Artificial intelligence |
Data structures (Computer science) |
Information theory |
Operations Research and Decision Theory |
Socio-Economic Policy |
Machine Learning |
Artificial Intelligence |
Data Structures and Information Theory |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Chapter 1: Introduction -- Chapter 2 : Natural Language Models -- Chapter 3: Large Language Models -- Chapter 4 : Macroeconomic Indicators, Aggregates, and Framework -- Chapter 5 : Economic Sustainability -- Chapter 6 : Social Sustainability -- Chapter 7: Conclusion. |
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Sommario/riassunto |
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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 |
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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. |
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