Flexible knowledge representation and new similarity measure: Application on case based reasoning for waste treatment

In Case Based Reasoning the representation of a case and the similarity measures are two difficult steps in the conception of a system. Often, these steps are developed to resolve one kind of problem. However, in some of them such as recovery treatment processes generation, it is necessary for the system to be able to modify and adapt the representation of a case and the similarity measures with respect of the context and also the kind of solutions proposed. In this paper, authors introduce a new method to represent cases with a flexibility based on a structure in a connectionist model. This flexibility is needed due to the complexity of cases, the number of possible options and to ensure the durability of the system. In a second main contribution, authors introduce a method for the selection of source cases using abstraction, conceptualisation and inference mechanisms. Finally, authors test their system in a CBR developed on SWI-Prolog with different problems. The CBR is applied to find new recovery processes and try to estimate the new upgraded product generated

The role of business intelligence in organizational memory supporti

Dissertation Report Master in Information SystemNowadays, in all organizations the major challenge issue facing managers is that they must give the appropriate decisions in a fluctuating environment while the information seems very hard to recognize whether it is good or bad. However, the actions that result of the decisions made will lead the organization to be in a thriving or declining position. That is why the leaders of organization really do not want to take wrong decisions. In order to minimize the risks, the managers should use the collective knowledge and experiences sharing through the Organizational Memory effectively to reduce the rate of unsuccessful decision making. Moreover, the BI systems are also a managerial concept and tools to allow their business to improve the effectiveness of decision making and problem solving. In the light of these motivations, the aim of this dissertation is to comprehend the role of the BI systems in supporting the system of Organizational Memories more effectively in the real context of crowdsourcing initiative called CrowdUM.