Survey of Process of Data Discovery and Environmental Decision Support Systems-Reference-Cited by-同舟云学术

Survey of Process of Data Discovery and Environmental Decision Support Systems

Published:2021-05-30 Issue:7 Volume:10 Page:46-50
ISSN:2278-3075
Container-title:Regular issue
language:en
Short-container-title:IJITEE

Author:

Altaf* Alaoui¹,Ibara Boris Olengoba²,Ettaki Badia³,Jamal Zerouaoui¹

Affiliation:

1. Laboratory of Materials Physics and Subatomics. Faculty of Sciences- Ibn Tofail University, Kenitra, Morocco.

2. Laboratory of Ecology and Environment, Faculty of Sciences Ben M'sik, University Hassan II, Casablanca, Morocco.

3. Laboratory of Research in Computer Science, Data Sciences and Knowledge Engineering , School of Information Sciences Rabat, Morocco,

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.

Publisher

Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP

Subject

Electrical and Electronic Engineering,Mechanics of Materials,Civil and Structural Engineering,General Computer Science

Reference51 articles.

1. Fayyad, U. M., G. Piatetsky-Shapiro, P. Smyth, and Ft. Uthurusamy, 1996. Advances in Knowledge Discovery and Data Mining, (AKDDM), AAAI/MIT Press.

2. Fayyad, U.M., Haussler, D. and Stolorz, Z. 1996. KDD for Science Data Analysis; Issues and Examples. Proc. 2nd Int. Conj. on Knowledge Discovery and Data Mining (KDD-96), Menlo Park, CA: AAAI Press.

3. Fayyad, U.M., Piatetsky-Shapiro, G., and Smyth, P. 1996. From Data Mining to Knowledge Discovery: An Overview, in AI(DDM, AAAI/MIT Press, pp. 1-30

4. D. A. Swayne, R. Denzer, L. Lilburne, M. Purvis, N. W. T. Quinn, and A. Storey, "?," in Environmental Software Systems, vol. 39, R. Denzer, D. A. Swayne, M. Purvis, and G. Schimak, Eds. Boston, MA: Springer US, 2000, pp. 259-268.

5. U. Baizyldayeva, O. K. Vlasov, A. A. Kuandykov, and T. B. Akhmetov, "Multi-Criteria Decision Support Systems. Comparative Analysis," 2013.

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Urban Sprawl and COVID-19 Impact Analysis by Integrating Deep Learning with Google Earth Engine;Remote Sensing;2022-04-24