Multi-feature fusion friend recommendation algorithm based on complex network

被引:0
作者
Pan K. [1 ]
Chen H. [2 ]
Liu Q. [2 ]
Wang J. [3 ]
Pu Y. [2 ]
Yin C. [1 ]
Yang Z. [1 ]
Zhao N. [1 ,2 ]
机构
[1] Electric Power Research Institute, Yunnan Power Grid Co., Ltd., Kunming
[2] School of Software, Yunnan University, Kunming
[3] College of Information Engineering and Automation, Kunming University of Science and Technology, Kunming
关键词
complex network; friend recommendation; multi-feature; node importance; social network;
D O I
10.1504/IJICT.2023.134831
中图分类号
学科分类号
摘要
At present, one of the problems of friend recommendation algorithms used in most social networks is that these networks often rely on a single index for recommendation. To solve this problem, multi-feature fusion (MFF) algorithm, a social network friend recommendation algorithm based on complex network theory, is proposed. The recommendation algorithm works by firstly divides the existing social networks into different communities. The importance of nodes in a social network is then calculated through the fusion of nodes’ importance information. Lastly, by integrating node importance information, friend number information and the shortest path information features are comprehensively evaluated, so as to generate final friend recommendation list. Simulation shows that with the increase of network nodes, the MFF algorithm outperforms common friend (CF) algorithm and friend similarity (FS) algorithm over all evaluation indicators including P-value, R-value and F1-value. Copyright © 2023 Inderscience Enterprises Ltd.
引用
收藏
页码:401 / 423
页数:22
相关论文
共 50 条
[31]   Implicit sentiment analysis based on multi-feature neural network model [J].
Zhuang, Yin ;
Liu, Zhen ;
Liu, Ting-Ting ;
Hung, Chih-Chieh ;
Chai, Yan-Jie .
SOFT COMPUTING, 2022, 26 (02) :635-644
[32]   Implicit sentiment analysis based on multi-feature neural network model [J].
Yin Zhuang ;
Zhen Liu ;
Ting-Ting Liu ;
Chih-Chieh Hung ;
Yan-Jie Chai .
Soft Computing, 2022, 26 :635-644
[33]   A friend recommendation algorithm based on the user relationship [J].
Shen, Qi ;
Wang, Sibo ;
Wang, Ran ;
Cao, Ke .
PROCEEDINGS OF THE 2016 3RD INTERNATIONAL CONFERENCE ON MATERIALS ENGINEERING, MANUFACTURING TECHNOLOGY AND CONTROL, 2016, 67 :1533-1538
[34]   A friend recommendation algorithm based on trajectory mining [J].
Cui, Bolong .
PROCEEDINGS OF 2016 9TH INTERNATIONAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE AND DESIGN (ISCID), VOL 2, 2016, :338-341
[35]   Research on Multi-Feature Front Vehicle Detection Algorithm based on Video Image [J].
Qu Shiru ;
Li Xu .
PROCEEDINGS OF THE 28TH CHINESE CONTROL AND DECISION CONFERENCE (2016 CCDC), 2016, :3831-3835
[36]   A Novel Microgrid Islanding Detection Algorithm Based on a Multi-Feature Improved LSTM [J].
Xia, Yan ;
Yu, Feihong ;
Xiong, Xingzhong ;
Huang, Qinyuan ;
Zhou, Qijun .
ENERGIES, 2022, 15 (08)
[37]   Collaborative Filtering Recommendation Algorithm Based on Multi-relationship Social Network [J].
Liu Y. ;
Yang H. ;
Sun G. ;
Bin S. .
Yang, Hua (yanghua@kfu.edu.cn), 2020, International Information and Engineering Technology Association (25) :359-364
[38]   A Dynamic Trust Relations-Based Friend Recommendation Algorithm in Social Network Systems [J].
Xue, Yun .
TEHNICKI VJESNIK-TECHNICAL GAZETTE, 2021, 28 (01) :185-192
[39]   Multi-Feature Fusion Transformer for Chinese Named Entity Recognition [J].
Han, Xiaokai ;
Yue, Qi ;
Chu, Jing ;
Han, Zhan ;
Shi, Yifan ;
Wang, Chengfeng .
2022 41ST CHINESE CONTROL CONFERENCE (CCC), 2022, :4227-4232
[40]   Generating Description with Multi-feature Fusion and Saliency Maps of Image [J].
Liu, Lisha ;
Ding, Yuxuan ;
Tian, Chunna ;
Yuan, Bo .
NINTH INTERNATIONAL CONFERENCE ON GRAPHIC AND IMAGE PROCESSING (ICGIP 2017), 2018, 10615