04140nam a22005535i 4500 978-3-031-55575-6 DE-He213 20251030112029.0 cr nn 008mamaa 240504s2024 sz | s |||| 0|eng d 9783031555756 978-3-031-55575-6 10.1007/978-3-031-55575-6 doi TA345-345.5 UN bicssc COM018000 bisacsh UN thema Transforming Public Services—Combining Data and Algorithms to Fulfil Citizen’s Expectations [electronic resource] / edited by Christophe Gaie, Mayuri Mehta. 1st ed. 2024. Cham : Springer Nature Switzerland : Imprint: Springer, 2024. VIII, 239 p. 69 illus., 39 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Intelligent Systems Reference Library, 1868-4408 ; 252 Digital Transformation of public services: Introduction, Current Trends and Future -- Enhancing Citizen Satisfaction Using Citizen-Facing Process Mining -- Thinking inside the Sandbox: Beyond public services digitalization with co-production -- Thinking inside the Sandbox: Beyond public services digitalization with co-production -- Usage of Modern API for automization of Government procedures -- Epidemiology inspired Cybersecurity Threats Forecasting Models applied to e-Government -- The provision of e-services by public administration bodies and their cybersecurity -- The provision of e-services by public administration bodies and their cybersecurity -- Fuzzy Logic Architecture for Availing the E-Governance Health Care Services by Rural Citizens -- Enhancing the efficiency and the security of e-Government: the French case study of human resources applications. This book provides a precise portrayal of the current trends and future perspectives of e-Government. It outlines new approaches that optimize public services across diverse sectors. Going beyond traditional boundaries, it offers mathematical models for public services supported by convincing case studies. This book significantly enhances various government services, such as education, healthcare, safety, security, and culture. It also strongly emphasizes safeguarding citizens' personal data, ensuring privacy, and obtaining explicit consent. Tailored for students and academics, the book is an invaluable reference for teaching graduate courses in e-Government, Process Modelling, or Artificial Intelligence. Its impact extends beyond the classroom; civil servants from all domains can find practical insights to navigate the ongoing modernization of public services. Even citizens curious about the transformation in their public services can find this book enlightening. Researchers working in the area of e-Governance can use this book to discover the recent developments in e-Government. Engineering Data processing. Computational intelligence. 64052 Big data. 57216 Data Engineering. 66059 Computational Intelligence. 64052 Big Data. 57216 Gaie, Christophe. editor. edt http://id.loc.gov/vocabulary/relators/edt 76414 Mehta, Mayuri. editor. edt http://id.loc.gov/vocabulary/relators/edt 76415 SpringerLink (Online service) Springer Nature eBook Printed edition: 9783031555749 Printed edition: 9783031555763 Printed edition: 9783031555770 Intelligent Systems Reference Library, 1868-4408 ; 252 67034 https://doi.org/10.1007/978-3-031-55575-6 ZDB-2-INR ZDB-2-SXIT 59661 59661