Posterior probability and collaborative filtering based Heterogeneous Recommendations model for user/item Application in use case of IoVT. (January 2023)

• Record Type: Journal Article
• Authors: Hai, Tao; Zhou, Jincheng; Lu, Ye; Jawawi, Dayang N．A．; Sinha, Anurag; Bhatnagar, Yash; Anumbe, Noble
• Is Part Of: Computers & electrical engineering. Volume 105(2023)
• Publication Date: 2023-01
• Subjects: Blockchain -- Next Basket Recommendation -- Recommender systems -- Cloud system; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2022.108532
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: Intuitive context-aware algorithms called "Next Basket recommender systems" improve consumers' decision-making by offering suggestions for potential products they might like to buy next based on their past behaviour. Even though it is now well-known, this field is still young. Many different industries, such as e-commerce and healthcare, employ recommender systems. Even though these datasets frequently contain sensitive data, most recommender systems place a greater emphasis on the models' accuracy than on their security and privacy. We investigate this concept in the context of the sequential recommendation job known as Next Basket Recommendation (NBR), whose objective is to provide a user with a selection of goods based on their purchasing behaviour. A recent state-of-the-art technology is blockchain. Blockchain creates a trusted environment without the involvement of a third party, thus ensuring privacy and security. It is designed in such a way that it is enough in itself to create trust. In this paper, we propose and assimilate an authentic blockchain privacy system for a fortified user recommendation system for the Next Basket Recommendation. With next basket proposals based on blockchain for safe transactions and distributed context-based processing, this suggested system enables the development of decentralized RSs. Through the use of atomic swaps on the blockchain, this effort aims to provide viable solutions that can lead to fair procedures. It places a focus on effective data deletion procedures that preserve user privacy and transfers the issue of decremental learning to the Next Basket system, a more secure and wise recommendation. By incorporating blockchain into recommender systems (RSs), which contain smart contracts in the main blockchain-based RS protocol, it is feasible to create safe trust-based systems with the benefit of multi-party computation backed by blockchain. Additionally, it aids in protecting user information since blockchain enables the secure processing of customer data in online portals.