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Context-aware recommendation system using graph-based behaviours analysis
journal contribution
posted on 2023-05-21, 16:02 authored by Zhang, L, Xiang LiXiang Li, Li, W, Zhou, H, Quan BaiQuan BaiRecommendation systems have been extensively studied over the last decade in various domains. It has been considered a powerful tool for assisting business owners in promoting sales and helping users with decision-making when given numerous choices. In this paper, we propose a novel Graph-based Context-Aware Recommendation Systems with Knowledge Graph to analyse and predict users’ behaviours, i.e., making recommendations based on historical events and their implicit associations. The model incorporates contextual information extracted from both users’ historical behaviours and events relations, where the contexts have been modelled as knowledge graphs. By leveraging the advantages offered from the knowledge graph, events dependencies and their subtle relations can be established and have been introduced in the recommendation process. Experimental results indicate that the proposed approach can outperform the state-of-the-art algorithms and achieve more accurate recommendations.
History
Publication title
Journal of Systems Science and Systems EngineeringVolume
30Issue
4Pagination
482-494ISSN
1861-9576Department/School
School of Information and Communication TechnologyPublisher
SpringerPlace of publication
GermanyRepository Status
- Restricted