Open Access
2013 Multiangle Social Network Recommendation Algorithms and Similarity Network Evaluation
Jinyu Hu, Zhiwei Gao, Weisen Pan
J. Appl. Math. 2013(SI19): 1-8 (2013). DOI: 10.1155/2013/248084

Abstract

Multiangle social network recommendation algorithms (MSN) and a new assessment method, called similarity network evaluation (SNE), are both proposed. From the viewpoint of six dimensions, the MSN are classified into six algorithms, including user-based algorithm from resource point (UBR), user-based algorithm from tag point (UBT), resource-based algorithm from tag point (RBT), resource-based algorithm from user point (RBU), tag-based algorithm from resource point (TBR), and tag-based algorithm from user point (TBU). Compared with the traditional recall/precision (RP) method, the SNE is more simple, effective, and visualized. The simulation results show that TBR and UBR are the best algorithms, RBU and TBU are the worst ones, and UBT and RBT are in the medium levels.

Citation

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Jinyu Hu. Zhiwei Gao. Weisen Pan. "Multiangle Social Network Recommendation Algorithms and Similarity Network Evaluation." J. Appl. Math. 2013 (SI19) 1 - 8, 2013. https://doi.org/10.1155/2013/248084

Information

Published: 2013
First available in Project Euclid: 14 March 2014

zbMATH: 1271.91090
MathSciNet: MR3082048
Digital Object Identifier: 10.1155/2013/248084

Rights: Copyright © 2013 Hindawi

Vol.2013 • No. SI19 • 2013
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