A Data Mining Approach for a Dynamic Development of an Ontology-Based Statistical Information System
| Autor: | Mohamed Hachem Kermani, Zizette Boufaida, Amel Lina Bensabbane, Besma Bourezg |
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| Jazyk: | angličtina |
| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | Journal of Information Science Theory and Practice, Vol 11, Iss 1 (2023) |
| Druh dokumentu: | article |
| ISSN: | 2287-9099 2287-4577 |
| DOI: | 10.1633/JISTaP.2023.11.2.5 |
| Popis: | This paper presents a dynamic development of an ontology-based statistical information system supporting the collection, storage, processing, analysis, and the presentation of statistical knowledge at the national scale. To accomplish this, we propose a data mining technique to dynamically collect data relating to citizens from publicly available data sources; the collected data will then be structured, classified, categorized, and integrated into an ontology. Moreover, an intelligent platform is proposed in order to generate quantitative and qualitative statistical information based on the knowledge stored in the ontology. The main aims of our proposed system are to digitize administrative tasks and to provide reliable statistical information to governmental, economic, and social actors. The authorities will use the ontology-based statistical information system for strategic decision-making as it easily collects, produces, analyzes, and provides both quantitative and qualitative knowledge that will help to improve the administration and management of national political, social, and economic life. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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