A Secured Movie Recommendation System using Decentralized Blockchain Network
Paper
Paper/Presentation Title | A Secured Movie Recommendation System using Decentralized Blockchain Network |
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Presentation Type | Paper |
Authors | Abduljabbar, Tamara Abdulmunim, Tao, Xiaohui, Zhang, Ji, Yong, Jianming and Zhou, Xujuan |
Journal or Proceedings Title | Proceedings of the 9th International Conference on Behavior, Economic and Social Computing (BESC 2022) |
Number of Pages | 6 |
Year | 2022 |
Publisher | IEEE (Institute of Electrical and Electronics Engineers) |
Place of Publication | United States |
ISBN | 9798350398144 |
Digital Object Identifier (DOI) | https://doi.org/10.1109/BESC57393.2022.9995357 |
Web Address (URL) of Paper | https://ieeexplore.ieee.org/document/9995357 |
Web Address (URL) of Conference Proceedings | https://ieeexplore.ieee.org/xpl/conhome/9994792/proceeding |
Conference/Event | 9th International Conference on Behavior, Economic and Social Computing (BESC 2022) |
Event Details | 9th International Conference on Behavior, Economic and Social Computing (BESC 2022) Parent International Conference on Behavioral, Economic and Socio-cultural Computing (BESC) Delivery In person Event Date 29 Oct 0202 to end of 31 Oct 2022 Event Location Matsuyama, Japan |
Abstract | Recommender systems strongly affect a company’s profitability and regularly play a significant role in the success of companies’ sales policies. The companies are now collecting vast amounts of user information to make sure they can use recommender systems and related algorithms for recommending products and services according to customer needs, preferences, and likenesses. Unfortunately, privacy concerns prevent users from sharing data generously with interested companies, even if the quality of the recommendations would be improved. One way to overcome privacy-related issues is using a secured solution such as incorporating blockchain technologies for privacy-based applications. Blockchain is a distributed system and has a peer-to- peer linked structure. Integrating blockchain technology and the Internet of Things creates modern decentralized systems. The integration gives scalability and security to recommender systems. This research calls for innovative and advanced research on Blockchain and recommendation systems. We constructed a blockchain-based recommender system using “the Movielens” database. Learning case studies include a model to recommend movies to users. The accuracy of models is evaluated by an incentive mechanism that offers a fully trust-based recommendation system with acceptable performance. The results demonstrate that blockchain-based methods can be efficiently used for the privacy preservation of recommender systems. |
Keywords | Recommender systems; Ethereum; Decentralized system; Privacypreserving; Blockchain |
ANZSRC Field of Research 2020 | 460999. Information systems not elsewhere classified |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | University of Southern Queensland |
https://research.usq.edu.au/item/z58y2/a-secured-movie-recommendation-system-using-decentralized-blockchain-network
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