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Record Nr. |
UNINA9910640385403321 |
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Autore |
Theocharis Stamatios |
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Titolo |
Semantic knowledge modelling via open linked ontologies : ontologies in e-governance / / Stamatios Theocharis and George A. Tsihrintzis |
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Pubbl/distr/stampa |
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Cham, Switzerland : , : Springer, , [2023] |
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©2023 |
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ISBN |
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Edizione |
[1st ed. 2023.] |
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Descrizione fisica |
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1 online resource (381 pages) |
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Collana |
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Artificial Intelligence-Enhanced Software and Systems Engineering, , 2731-6033 ; ; 4 |
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Disciplina |
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Soggetti |
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Deep learning (Machine learning) |
Internet in public administration |
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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 contenuto |
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Introduction -- e-Government: The concept, the environment & critical issues for the Back-Office systems -- Semantic Web: The evolution of the Web & the opportunities for the e-Government -- Representation and knowledge management for the benefit of e-Government - Opportunities through the tools of the Semantic Web -- Towards Open Data and Open Governance – Representation of knowledge and Triplification of data in the field of the Greek Open Government Data -- Production and publication of linked open data: The case of open ontologies -- Education and E-Government - The case of a Moodle based platform for the education and evaluation of civil servants -- Conclusions – Future Work. |
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Sommario/riassunto |
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Evolving technological advances in Artificial Intelligence-empowered Software present significant potential to lead e-Government towards more collective efforts, exchange of experiences on best practices both at national and international levels and dissemination of secluded administrative knowledge. In this book, novel semantic web-based and linked open data-based approaches are developed for the modelling and management of the huge volume of administrative data and the procedures followed by public sector bodies and for the production and management of relevant administrative knowledge. The book consists of eight chapters, each of which includes relevant bibliographic |
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references for deeper probing. Appendices complement this work with sections of configuration files of the applications developed and used. Professors, researchers, scientists, engineers and students in artificial intelligence, e-government and other computer science-related disciplines are expected to benefit greatly from it, along with non-specialist readers from other disciplines who are interested in getting versed in the recent developments in e-government. |
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