Research Article
Artificial Intelligence based Composition for E-Government Services
@INPROCEEDINGS{10.4108/eai.24-4-2019.2284071, author={amina adadi and Mohammed BERRADA and Nabil EL AKKAD}, title={Artificial Intelligence based Composition for E-Government Services }, proceedings={Proceedings of the Third International Conference on Computing and Wireless Communication Systems, ICCWCS 2019, April 24-25, 2019, Faculty of Sciences, Ibn Tofa\~{n}l University -K\^{e}nitra- Morocco}, publisher={EAI}, proceedings_a={ICCWCS}, year={2019}, month={5}, keywords={semantic web service composition e-government ontology multi-agent systems ai planning machine learning reinforcement learning}, doi={10.4108/eai.24-4-2019.2284071} }- amina adadi
Mohammed BERRADA
Nabil EL AKKAD
Year: 2019
Artificial Intelligence based Composition for E-Government Services
ICCWCS
EAI
DOI: 10.4108/eai.24-4-2019.2284071
Abstract
Given the complex nature of the public sector with several distributed governmental institutions and manifold semantic differences of interpretation, the achievement of interoperability and integration is a key challenge for a comprehensive and effective Electronic Government (e-Government). Promising technologies that could be used to tackle this issue are: the powerful concept of ontology and the advanced Artificial Intelligence (AI) systems. Ontologies contribute to a common understanding of heterogeneous resources, while AI techniques make process integration dynamic and automated. However, up until now the use of AI along with ontologies has been fairly limited in e-Government. There is still, then, untapped potential in this field which worth to be exploited. In this paper, we present a dynamic approach for semantically integrating e-Government Web services based on AI techniques. The overall objective of our approach is to improve the citizen centric e-Government vision by providing a conceptual framework for automatically discovering, composing and optimizing e-Government services. Within the proposed approach, special emphasis is put on personalization aspects and evaluation criteria for e-Government platform.