Publication Type : Journal Article
Publisher : Emerald logo
Source : Data Technologies and Applications (2022). https://doi.org/10.1108/DTA-07-2021-0182 . (SCI-E, Impact Factor:1.667).
Url : https://doi.org/10.1108/DTA-07-2021-0182
Campus : Coimbatore
School : School of Computing
Year : 2022
Abstract : In a multi-stakeholder recommender system (MSRS), stakeholders are the multiple entities (consumer, producer, system, etc.) benefited by the generated recommendations. Traditionally, the exclusive focus on only a single stakeholders' (for example, only consumer or end-user) preferences obscured the welfare of the others. Two major challenges are encountered while incorporating the multiple stakeholders' perspectives in MSRS: designing a dedicated utility function for each stakeholder and optimizing their utility without hurting others. This paper proposes multiple utility functions for different stakeholders and optimizes these functions for generating balanced, personalized recommendations for each stakeholder.
Cite this Research Publication : R. Shrivastava, D.S. Sisodia, N.K. Nagwani , Utility optimization-based multi-stakeholder personalized recommendation system, Data Technologies and Applications (2022). https://doi.org/10.1108/DTA-07-2021-0182 . (SCI-E, Impact Factor:1.667).