Titlebook: Electronic Government and the Information Systems Perspective; 10th International C Andrea K?,Enrico Francesconi,Ismail Khalil Conference p

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我要沮喪

Conference proceedings 2021resented were carefully reviewed and selected from 21 submissions and focus on information systems and ICT aspects of e-government. The papers are organized in 3 topical sections: e-government theoretical background and cases; identity management and legal issues; artificial intelligence and machine learning in e-government context.

紳士

,The PCE’s Long Road to Democracy 1954–77,n two countries: France and Italy..This analysis makes it possible to trace the evolution of these policies and highlight their critical importance in applying the data minimization principle and in enforcing the right to erasure under Art. 17 GDPR.

跑過

Maroesjka van Nieuwenhuijzen,Christel Elias study contributes through a uniform understanding of public service platforms. Despite constitutive elements, the proposed framework for platforms in the public sector may guide future analysis. The analysis framework is applied to platforms of federal states in the European Union.

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虛假

In Search of Marie-Antoinette in the 1930shms predominantly classified the tweets as “neutral”, that is, these posts do not explicitly expose their users’ opinion about the topic. Of the tweets that showed polarity, there was a dominance of posts classified as “positive”, i.e., their authors have positive feelings (support, affinity) concerning the Social Security Reform proposal.

fringe

https://doi.org/10.1007/978-3-642-95481-8hese four latent features. We identify taxpayers located at the boundary of each cluster by using kernel density estimation, which is further investigated to single out tax evaders. We applied our method to the iron and steel taxpayers data set provided by the Commercial Taxes Department, the government of Telangana, India.

Range-Of-Motion

The Province and Function of Peace Researchmization techniques. The results achieved good success rates. Results for XGBoost using balanced data showed a recall of 89.3% and unbalanced data 87.8%. However, for unbalanced data, the AUC score was 98.1%, against 97.9% for balanced data.