A Personalized Recommender System Based-on Knowledge Graph Embeddings

• URL: http://arxiv.org/abs/2307.10680v1
• Date: Thu, 20 Jul 2023 08:14:06 GMT
• Title: A Personalized Recommender System Based-on Knowledge Graph Embeddings
• Authors: Ngoc Luyen Le (Heudiasyc), Marie-H\'el\`ene Abel (Heudiasyc), Philippe Gouspillou
• Abstract summary: The recent emergence in interest for using knowledge graphs as a form of information modeling has led to their increased adoption in recommender systems. By incorporating relevant users and relevant items into the knowledge graph, these systems can better capture the implicit connections between them and provide more accurate recommendations.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Knowledge graphs have proven to be effective for modeling entities and their relationships through the use of ontologies. The recent emergence in interest for using knowledge graphs as a form of information modeling has led to their increased adoption in recommender systems. By incorporating users and items into the knowledge graph, these systems can better capture the implicit connections between them and provide more accurate recommendations. In this paper, we investigate and propose the construction of a personalized recommender system via knowledge graphs embedding applied to the vehicle purchase/sale domain. The results of our experimentation demonstrate the efficacy of the proposed method in providing relevant recommendations that are consistent with individual users.

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