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Innovations in Bio-inspired Computing and Applications

Volume 237 of the series Advances in Intelligent Systems and Computing pp 201-213

An Intelligent Multi-agent Recommender System

  • Mahmood A. MahmoodAffiliated withISSR, Computer Sciences and Information Dept., Cairo UniversityScientific Research Group in Egypt (SRGE) Email author 
  • , Nashwa El-BendaryAffiliated withArab Academy for Science, Technology, and Maritime Transport
  • , Jan PlatošAffiliated withDepartment of Computer Science, VSB-Technical University of Ostrava
  • , Aboul Ella HassanienAffiliated withScientific Research Group in Egypt (SRGE)Information Technology Dept., Faculty of Computers and Information, Cairo University
  • , Hesham A. HefnyAffiliated withISSR, Computer Sciences and Information Dept., Cairo UniversityScientific Research Group in Egypt (SRGE)

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Abstract

This article presents a Multi-Agent approach for handling the problem of recommendation. The proposed system works via two main agents; namely, the matching agent and the recommendation agent. Experimental results showed that the proposed rough mereology based Multi-agent system for solving the recommendation problem is scalable and has possibilities for future modification and adaptability to other problem domains. Moreover, it succeeded in reducing the information overload while recommending relevant decisions to users. The system achieved high accuracy in ranking using users profile and information system profiles. The resulted value of the Mean Absolute Error (MAE) is acceptable compared to other recommender systems applied other computational intelligence approaches.

Keywords

rough mereology multi-agent recommender system