Please wait a minute...
Computer & Telecommunication  2024, Vol. 1 Issue (6): 7-10    DOI: 10.15966/j.cnki.dnydx.2024.06.008
Current Issue | Archive | Adv Search |
TrustOCCR: Social One Class Collaborative Ranking Recommendation Algorithm by Trust
Shunde Polytechnic
Download:
Export: BibTeX | EndNote (RIS)      
Abstract   The problem with previous studies of social One Class Collaborative Ranking (OCCR) algorithms is that they simply integrated the user's social network information into their model, without taking into account the transmission of social trust networks between users. To solve this problem, a new social one class collaborative ranking recommendation algorithm (TrustOCCR) based on CLiMF model and the newest TrustMF model is proposed, which aims to improve the performance of social one class collaborative ranking recommendation by integrating twofold sparse data, i.e., implicit feedback data and the transitive social trust network data. Experimental results on practical dataset show that our proposed TrustOCCR algorithm outperformed existing state-of-the-art OCCF approach over di?erent evaluation metrics, and that the TrustOCCR algorithm possesses good expansibility and is suitable for processing big data in the ?eld of internet information recommendation. 
Key wordsrecommendation system      collaborative ?ltering      social collaborative ranking      social network     
Published: 01 November 2024

Cite this article:

LI Gai GUO Ze-hao. TrustOCCR: Social One Class Collaborative Ranking Recommendation Algorithm by Trust. Computer & Telecommunication, 2024, 1(6): 7-10.

URL:

https://www.computertelecom.com.cn/EN/10.15966/j.cnki.dnydx.2024.06.008     OR     https://www.computertelecom.com.cn/EN/Y2024/V1/I6/7

[1] OU Wei-hong YANG Yong-qin. Research on the Book Recommendation System Based on Mahout under the Big Data Platform[J]. 电脑与电信, 2021, 1(9): 28-31.
[2] GENG Yi-wen. Research on Recommendation System Based on StackedAutoencoder[J]. 电脑与电信, 2020, 1(11): 65-70.
[3] CHEN Bo-lun, HUA Yong, YUAN Yan, LI Fen-fen, ZHANG Zheng-wei. Discussion on the Influence Maximization of Social Network in the Teaching of Information Technology in Universities[J]. 电脑与电信, 2018, 1(3): 1-3.
[4] LV Hai-yan. Research on the Recommendation System of Motorcycle Logistics Scale Control Based on User Behaviors-A Case for Motorcycle Logistics in Pearl River Delta of China [J]. 电脑与电信, 2018, 1(11): 18-21.
[5] Chen Zebo. Research on the Application of Collaborative Filtering Recommendation System Based on Classification[J]. 电脑与电信, 2015, 1(9): 60-62.
[6] Chen Hang. Design of Tag Recommendation System Based on Hadoop[J]. 电脑与电信, 2015, 1(7): 59-61.
[7] Zhu Yinghui. Design and Analysis on ClassBook for Cultural Exchange in University Campus[J]. 电脑与电信, 2015, 1(3): 53-59.
Copyright © Computer & Telecommunication, All Rights Reserved.
Powered by Beijing Magtech Co. Ltd