دورية أكاديمية

Sparse Trust Data Mining

التفاصيل البيبلوغرافية
العنوان: Sparse Trust Data Mining
المؤلفون: Nie, Pengli, Xu, Guangquan, Jiao, Litao, Liu, Shaoying, Liu, Jian, Meng, Weizhi, Wu, Hongyue, Feng, Meiqi, Wang, Weizhe, Jing, Zhengjun, Zheng, Xi
المصدر: Nie , P , Xu , G , Jiao , L , Liu , S , Liu , J , Meng , W , Wu , H , Feng , M , Wang , W , Jing , Z & Zheng , X 2021 , ' Sparse Trust Data Mining ' , IEEE Transactions on Information Forensics and Security , vol. 16 , no. 99 , pp. 4559-4573 . https://doi.org/10.1109/TIFS.2021.3109412Test
سنة النشر: 2021
المجموعة: Technical University of Denmark: DTU Orbit / Danmarks Tekniske Universitet
مصطلحات موضوعية: Anti-sparsification, Recommendation system, Sparse trust, Trust model
الوصف: As recommendation systems continue to evolve, researchers are using trust data to improve the accuracy of recommendation prediction and help users find relevant information. However, large recommendation systems with trust data suffer from the sparse trust problem, which leads to grade inflation and severely affects the reliability of trust propagation. This paper presents a novel research on sparse trust data mining, which includes the new concept of sparse trust, a sparse trust model, and a trust mining framework. It lays a foundation for the trust-related research in large recommended systems. The new trust mining framework is based on customized normalization functions and a novel transitive gossip trust model, which discovers potential trust information between entities in a large-scale user network and applies it to a recommendation system. We conducts a comprehensive performance evaluation on both real-world and synthetic datasets. The results confirm that our framework mines new trust and effectively ameliorates sparse trust problem.
نوع الوثيقة: article in journal/newspaper
وصف الملف: application/pdf
اللغة: English
العلاقة: https://orbit.dtu.dk/en/publications/d5416ced-1fb2-4571-a6a5-747ca9615325Test
DOI: 10.1109/TIFS.2021.3109412
الإتاحة: https://doi.org/10.1109/TIFS.2021.3109412Test
https://orbit.dtu.dk/en/publications/d5416ced-1fb2-4571-a6a5-747ca9615325Test
https://backend.orbit.dtu.dk/ws/files/259137906/HKKR_Sparse_Trust_Data_Mining.pdfTest
حقوق: info:eu-repo/semantics/openAccess
رقم الانضمام: edsbas.E6E6B1F8
قاعدة البيانات: BASE