@conference{Alexopoulos2019,
title = {How Machine Learning is Changing e-Government},
author = {Charalampos Alexopoulos and Zoi Lachana and Aggeliki Androutsopoulou and Vasiliki Diamantopoulou and Yannis Charalabidis and Michalis Avgerinos Loutsaris},
url = {http://www.icsd.aegean.gr/publication_files/Conference/583212650.pdf},
year = {2019},
date = {2019-04-01},
pages = {10},
abstract = {Big Data is, clearly, an integral part of modern information societies. A vast amount of data is, daily, produced and it is estimated that, for the years to come, this number will grow dramatically. In order for transforming this hidden provided information into a useful one, the use of advanced technologies, such as Machine Learning is deemed appropriate. Over the last years, Machine Learning has grown a great effort considering the given opportunities its usage provides. Furthermore, Machine Learning is a technology that can handle Big Data classification for statistical or even more complex purposes such as decision making. At the same time the new generation of government, Government 3.0, explores all the new opportunities to tackle any challenge faced by contemporary societies by utilizing new technologies for data driven decision making. Taking into account the opportunities Machine Learning can provide, more and more governments participate in the development of such applications in different governmental domains. But is the Machine Learning only beneficial for public sectors? Although there is a huge number of researches in the literature there is no a comprehensive study towards the analysis of this technology. Our research moves towards this question conducting a comprehensive analysis of the use of Machine Learning from Governments. Through the analysis all benefits and barriers are indicated from the public sectors' perspective pinpointing, also, a number of Machine Learning applications where governments are involved.},
keywords = {Artificial Intelligence, Big Data, government 3.0, Government services, Machine Learning},
pubstate = {published},
tppubtype = {conference}
}
Big Data is, clearly, an integral part of modern information societies. A vast amount of data is, daily, produced and it is estimated that, for the years to come, this number will grow dramatically. In order for transforming this hidden provided information into a useful one, the use of advanced technologies, such as Machine Learning is deemed appropriate. Over the last years, Machine Learning has grown a great effort considering the given opportunities its usage provides. Furthermore, Machine Learning is a technology that can handle Big Data classification for statistical or even more complex purposes such as decision making. At the same time the new generation of government, Government 3.0, explores all the new opportunities to tackle any challenge faced by contemporary societies by utilizing new technologies for data driven decision making. Taking into account the opportunities Machine Learning can provide, more and more governments participate in the development of such applications in different governmental domains. But is the Machine Learning only beneficial for public sectors? Although there is a huge number of researches in the literature there is no a comprehensive study towards the analysis of this technology. Our research moves towards this question conducting a comprehensive analysis of the use of Machine Learning from Governments. Through the analysis all benefits and barriers are indicated from the public sectors' perspective pinpointing, also, a number of Machine Learning applications where governments are involved.
