Research Article
Trust Based Recommendation System Using Knowledge Graph (KGTRS)
@INPROCEEDINGS{10.4108/eai.24-3-2022.2318767, author={Nidhi B Channappagoudar and Richa Singh}, title={Trust Based Recommendation System Using Knowledge Graph (KGTRS)}, proceedings={Proceedings of the 3rd International Conference on ICT for Digital, Smart, and Sustainable Development, ICIDSSD 2022, 24-25 March 2022, New Delhi, India}, publisher={EAI}, proceedings_a={ICIDSSD}, year={2023}, month={5}, keywords={knowledge graph; trust; recommender systems; cold start; sparsity}, doi={10.4108/eai.24-3-2022.2318767} }- Nidhi B Channappagoudar
Richa Singh
Year: 2023
Trust Based Recommendation System Using Knowledge Graph (KGTRS)
ICIDSSD
EAI
DOI: 10.4108/eai.24-3-2022.2318767
Abstract
Recommender systems has proven its importance to the solution of exponentially increasing data on the internet, which provides users with more personalized services of information for better development of online services. The issue of trust has emerged into our day-to-day life since early 90s, which focuses on improvement of recommender systems. The Google Knowledge base gathers information from a variety of sources. In the presented work trust is incorporated using knowledge graph in order to improve the recommendation system that provide the opportunity to build trust with potential site visitors looking for a product/service/information. To enhance the user belief and usre acceptance trust based recommendation system is incorporated. Trust based recommender systems using knowledge graph improve the accuracy of the recommender system and user experience. They are also capable of handling some challenges of recommender systems such as cold-start problem.