An Effective Tool for the Experts' Recommendation Based on PROMETHEE II and Negotiation: Application to the Industrial Maintenance

• Main Authors: Nawal Sad Houari, Noria Taghezout
• Format: Article
• Language: English
• Published: Universidad Internacional de La Rioja (UNIR) 2021-05-01
• Series: International Journal of Interactive Multimedia and Artificial Intelligence
• Subjects: business processes; fuzzy; k-means; recommendation systems
• Online Access: https://www.ijimai.org/journal/bibcite/reference/2875

In this article, we propose an expert recommendation tool that relies on the skills of experts and their interventions in collaboration. This tool provides us with a list of the most appropriate (effective) experts to solve business problems in the field of industrial maintenance. The proposed system recommends experts using an unsupervised classification algorithm that takes into account the competences of the experts, their preferences and the stored information in previous collaborative sessions. We have tested the performance of the system with K-means and C-means algorithms. To fix the inconsistencies detected in business rules, the PROMETHEE II multi-criteria decision support method is integrated into the extended CNP negotiation protocol in order to classify the experts from best to worst. The study is supported by the well known petroleum company in Algeria namely SONATRACH where the experimentations are operated on maintenance domain. Experiments results show the effectiveness of our approach, obtaining a recall of 86%, precision of 92% and F-measure of 89%. Also, the proposed approach offers very high results and improvement, in terms of response time (154.28 ms), space memory (9843912 bytes) and negotiation rounds.