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Multi-criteria Group Recommender System Based on Analytical Hierarchy Process

  • Nirmal ChoudharyEmail author
  • K. K. Bharadwaj
Conference paper
  • 221 Downloads
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 141)

Abstract

Current researches have demonstrated that the significance of Multi-Criteria Decision-Making (MCDM) methods in Group Recommender Systems (GRSs) has yet to be thoroughly discovered. Thus, we have proposed a Multi-criteria GRS (MCGRS) to provide recommendations for group of users based on multi-criteria optimization. The idea behind our approach is that, each member in a group have different opinions about each criterion and he/she would try to make the best use of multi-criteria to fulfill his/her own preference in decision-making process. Therefore, we have employed Analytical Hierarchy Process (AHP) to learn the priority of each criterion to maximize the utility for each criterion. Then, MCGRS generate the most appropriate recommendation for the group. Experiments are performed on Yahoo! Movies dataset and the results of comparative analysis of proposed MCGRS with baseline GRSs techniques clearly demonstrate the supremacy of our proposed model.

Keywords

Recommendation mechanism Decision-making Multi-criteria group recommender systems Analytical hierarchy process 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.School of Computer and Systems SciencesJawaharlal Nehru UniversityNew DelhiIndia

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