Survey of Process of Data Discovery and Environmental Decision Support Systems
Altaf Alaoui1, Boris Olengoba Ibara2, Badia Ettaki3, Jamal Zerouaoui4
1Alaoui Altaf*, Laboratory of Materials Physics and Subatomics. Faculty of Sciences- Ibn Tofail University, Kenitra, Morocco.
2Boris Olengoba Ibara, Laboratory of Ecology and Environment, Faculty of Sciences Ben M’sik, University Hassan II, Casablanca, Morocco.
3Badia Ettaki, Laboratory of Research in Computer Science, Data Sciences and Knowledge Engineering, School of Information Sciences Rabat, Morocco.
4Jamal Zerouaoui, Laboratory of Materials Physics and Subatomics. Faculty of Sciences- Ibn Tofail University, Kenitra, Morocco.
Manuscript received on May 06, 2021. | Revised Manuscript received on May 19, 2021. | Manuscript published on May 30, 2021. | PP: 46-50 | Volume-10 Issue-7, May 2021 | Retrieval Number: 100.1/ijitee.G89050510721| DOI: 10.35940/ijitee.G8905.0510721
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The process of data discovery is an approach to extracting knowledge, valid, and usable information from large amounts of data, using automatic or semi-automatic methods. This article is an inventory of the different information extraction processes encountered in the literature for different fields of application and for the development of environmental informatics. Following an analysis between the different models, we can summarize the existing models with a proposal for a process that exploits the strengths of the different processes.
Keywords: Knowledge Discovery in Databases, KDDM, Environmental Decision Support Systems, GIS, KBS, EDSS.