Automatic Classification and Analysis of Multiple-Criteria Decision Making
As part of the automatic decision-making process, we propose to highlight the importance of business intelligence and its contribution to management and decision-making in companies. The multi-criteria automatic analysis proposes to set up a complete computer chain that automates all the classic steps of the multi-criteria decision-making. The automatic multi-criteria decision relies mainly on the two learning techniques. Unsupervised classification is used to find two compact and well-separated groups in a dataset. Supervised classification is a learning method for automatically generating rules from a learning database. Both techniques must have existed to produce comprehensive and automatic classification procedures by the user. In this context, we will focus on showing how business intelligence, particularly through data mining and integrated software packages, can be an important decision-support tool for companies.
KeywordsBusiness intelligence Multi-criteria decision making Data analysts Data scientists
- 2.Loussaief, S., Abdelkrim, A.: Machine learning framework for image classification. In: 7th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT), pp. 58–61 (2016)Google Scholar
- 7.Derbel, A., Boujelbene, Y.: Road congestion analysis in the agglomeration of Sfax using a Bayesian model. In: Lecture Notes in Computer Science book series LNCS 11277, pp. 131–142 (2018)Google Scholar
- 8.Derbel, A., Boujelbene, Y.: Bayesian network for traffic management application: estimated the travel time. In: 2nd World Symposium on Web Applications and Networking (WSWAN) (2015)Google Scholar