@inproceedings{dd082fd4bea243bf870c5c200e76565d,
title = "A trust-enriched approach for item-based collaborative filtering recommendations",
abstract = "The item-based collaborative filtering (CF) is one of the most successful approaches utilized by the recommendation systems. The basic concept behind it is to recommend those items to users which are similar to other items that these users have been interested in recently. This paper proposes a hybrid method that integrates user trust relations with item-based CF. This is achieved by incorporating user social similarities into the computation of item similarities. Performance evaluation of the proposed method is done by comparing the results with the traditional item-based CF. The experiment results demonstrate that the proposed approach achieves better accuracy.",
keywords = "Collaborative filtering, Item recommendations, Item-based filtering, Social relations",
author = "Haiyang Zhang and Ivan Ganchev and Nikolov, {Nikola S.} and Mairtin O'droma",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 12th IEEE International Conference on Intelligent Computer Communication and Processing, ICCP 2016 ; Conference date: 08-09-2016 Through 10-09-2016",
year = "2016",
month = nov,
day = "7",
doi = "10.1109/ICCP.2016.7737124",
language = "English",
series = "Proceedings - 2016 IEEE 12th International Conference on Intelligent Computer Communication and Processing, ICCP 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "65--68",
editor = "Rodica Potolea and Slavescu, {Radu Razvan}",
booktitle = "Proceedings - 2016 IEEE 12th International Conference on Intelligent Computer Communication and Processing, ICCP 2016",
}