Journal of Shandong University(Engineering Science) ›› 2019, Vol. 49 ›› Issue (2): 42-46.doi: 10.6040/j.issn.1672-3961.0.2018.346

• Machine Learning & Data Mining • Previous Articles     Next Articles

Recommendation algorithm based on trust network reconfiguration

Yun HU1(),Shu ZHANG2,*(),Hui LI3,4,Kankan SHE1,Jun SHI3   

  1. 1. College of Information Technology, Nanjing University of Chinese Medicine, Nanjing 210023, Jiangsu, China
    2. Business School, Huaihai Institute of Technology, Lianyungang 222001, Jiangsu, China
    3. Department of Computer Science, Huaihai Institute of Technology, Lianyungang 222001, Jiangsu, China
    4. Marine Resources Development Institute of Jiangsu, Lianyungang 222005, Jiangsu, China
  • Received:2018-08-16 Online:2019-04-20 Published:2019-04-19
  • Contact: Shu ZHANG E-mail:1150290259@qq.com;shufanzs@126.com
  • Supported by:
    江苏高校“青蓝工程”培养对象;江苏省333人才培养工程;教育部协同育人项目(201702134005);教育部协同育人项目(201701028110);连云港市科技计划项目(JC1608);连云港市科技计划项目(CG1611);连云港市“521高层次人才培养工程”(RJFW-041);江苏省“六大人才高峰”资助项目(ZKK201604)

RichHTML

8

PDF (PC)

494

Abstract:

A new recommendation algorithm was investigated base on the problem of trust network reconfiguration. The initial trust network was constructed by combining the user similarity value with the trust relationship, and the initial prediction of the user's unrated items was carried out.A method based on reliability was used to evaluate the quality of prediction score. The unrated items were predicted according to the new user trust network. The performance was verified on two real data sets, which were Epinions dataset and Flixster dataset. The experimental results showed that the reconfiguration algorithm of trust network effectively solved the problem of data sparsity in recommendation system, and it was superior to the traditional recommendation algorithm in recall and precision ratio.

Key words: trust, collaborative filtering, social network, reconstruction, recommendation

CLC Number: 

  • TP391

Fig.1

Flow chart of the recommendation system"

Fig.2

The MAE results for different parameter θ"

Fig.3

The MAUE results for different parameter θ"

Fig.4

Comparaison results on the Epinion dataset"

Fig.5

Comparaison results on the Flixter dataset"

1 ZAMAN F , ELSAYED S M , RAY T , et al. Configuring two-algorithm-based evolutionary approach for solving dynamic economic dispatch problems[J]. Engineering Applications of Artificial Intelligence, 2016, 53 (1): 105- 125.
2 方耀宁, 郭云飞, 兰巨龙. 基于Logistic函数的贝叶斯概率矩阵分解算法[J]. 电子与信息学报, 2014, 36 (3): 715- 720.
FANG Yaoning , GUO Yunfei , LAN Juling . A bayesian probabilistic matrix factorization algorithm based on logistic function[J]. Journal of Electronics & Information Technology, 2014, 36 (3): 715- 720.
3 FAYOLLEAYOLLE P A , PASKOASKO A . An evolutionary approach to the extraction of object construction trees from 3D point clouds[M]. Butterworth-Heinemann, 2016.
4 SILVA E , CAMILO J , PASCOAL M L , et al. An evolutionary approach for combining results of recommender systems techniques based on collaborative filtering[J]. Expert Systems with Applications, 2016, 53 (2): 204- 218.
5 郭弘毅, 刘功申, 苏波, 等. 融合社区结构和兴趣聚类的协同过滤推荐算法[J]. 计算机研究与发展, 2016, 53 (8): 1664- 1672.
GUO Hongyi , LIU Gongshen , SU Bo . Collaborative filtering recommendation algorithm combing community structure and interest clusters[J]. Journal of Computer Research and Development, 2016, 53 (8): 1664- 1672.
6 GUO G , ZHANG J , SMITH N Y . Leveraging multiviews of trust and similarity to enhance clustering-based recommender systems[J]. Knowledge-Based Systems, 2017, 74 (1): 14- 27.
7 SHEUGH L , ALIZADEH S H . A novel 2D-graph clustering method based on trust and similarity measures to enhance accuracy and coverage in recommender systems[J]. Information Sciences, 2018, 432 (1): 210- 230.
8 涂丹丹, 舒承椿, 余海燕. 基于联合概率矩阵分解的上下文广告推荐算法[J]. 软件学报, 2015, (3): 454- 464.
TU Dandan , SHU Chengchun , YU Haiyan . Using unified probabilistic matrix factorization for contextual advertisement recommendation[J]. Journal of Software, 2015, (3): 454- 464.
9 XU J , ZHONG Y , ZHU W . Trust-based context-aware mobile social network service recommendation[J]. Wuhan University Journal of Natural Sciences, 2017, 22 (2): 149- 156.
doi: 10.1007/s11859-017-1228-3
10 SHI L , ZHAO W X , SHEN Y D . Local representative-based matrix factorization for cold-start recommendation[J]. Acm Transactions on Information Systems, 2017, 36 (2): 1- 28.
11 PIRASTEH P , HWANG D , & JUNG J . Exploiting matrix factorization to asymmetric user similarities in recommendation systems[J]. Knowledge-Based Systems, 2016, 83 (1): 51- 57.
12 FERNANDES B R , PLA F . Incremental probabilistic latent semantic analysis for video retrieval[J]. Image & Vision Computing, 2015, 38 (1): 1- 12.
13 YIN J , HO Q , XING E P . A scalable approach to probabilistic latent space inference of large-scale networks[J]. Advances in Neural Information Processing Systems, 2013, 2013 (1): 422- 430.
14 FITZGERALD J , GAMBLE C , PAYNE R , et al. Collaborative model-based systems engineering for cyber-physical systems, with a building automation case study[J]. Incose International Symposium, 2016, 26 (1): 817- 832.
doi: 10.1002/iis2.2016.26.issue-1
15 FEINBERG E A , KASYANOV P O , ZGUROVSKY M Z . Partially observable total-cost markov decision processes with weakly continuous transition probabilities[J]. Mathematics of Operations Research, 2016, 41 (2): 591- 607.
16 MORADI P , AHMADIAN S . A reliability-based recommendation method to improve trust-aware recommender systems[J]. Expert Systems with Applications, 2015, 42 (21): 7386- 7398.
doi: 10.1016/j.eswa.2015.05.027
17 NAZEMIN A, GHOLAMI H, TAGHIYAREH F. An improved model of trust-aware recommender systems using distrust metric[C]//International Conference on Advances in Social Networks Analysis and Mining. Istanbul, Turkey: IEEE, 2012: 1079-1084.
18 DENG S , HUANG L , XU G . Social network-based service recommendation with trust enhancement[J]. Expert Systems with Applications, 2014, 41 (2): 8075- 8084.
19 YANG X , GUO Y , LIU Y . Bayesian-inference-based recommendation in online social networks[J]. IEEE Transactions on Parallel and Distributed Systems, 2014, 24 (4): 642- 651.
20 GUO G , ZHANG J , THALMAN D . Merging trust in collaborative filtering to alleviate data sparsity and cold start[J]. Knowledge-Based Systems, 2014, 57 (1): 57- 68.
[1] Yijiang HE,Junping DU,Feifei KOU,Meiyu LIANG,Wei WANG,Ang LUO. Images auto-encoding algorithm based on deep convolution neural network [J]. Journal of Shandong University(Engineering Science), 2019, 49(2): 61-66.
[2] Chunlin QIAN,Xingfang ZHANG,Lihua SUN. Advanced collaborative filtering recommendation model based on sentiment analysis of online review [J]. Journal of Shandong University(Engineering Science), 2019, 49(1): 47-54.
[3] Guoxin WANG,Fengdong CHEN,Guodong LIU. Feature extraction method of color pseudo-random coded structured light [J]. Journal of Shandong University(Engineering Science), 2018, 48(5): 55-60.
[4] HE Wenjie, HE Weichao, SUN Quansen. Parallelization and GPU acceleration of compressive sensing reconstruction algorithm [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2018, 48(3): 110-114.
[5] DU Xixi, LIU Huafeng, JING Liping. An additive co-clustering for recommendation of integrating social network [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2018, 48(3): 96-102.
[6] DENG Junwu, ZHANG Yumin, ZHANG Hongdi, DU Xiaokun. Fault diagnosis and fault-tolerant control methods of X-tail UAV [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(5): 166-172.
[7] LI Minghu, LI Gang, ZHONG Maiying. Application of dynamic kernel principal component analysis in unmanned aerial vehicle fault diagnosis [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(5): 215-222.
[8] LIU Zhuo, WANG Tianzhen, TANG Tianhao, FENG Yefan, YAO Junqi, GAO Diju. A fault diagnosis and fault-tolerant control strategy for multilevel inverter [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(5): 229-237.
[9] WANG Xin, LU Jingya, WANG Ying. Exploring user interest expansion method for recommendation [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(2): 71-79.
[10] WANG Zhiqiang, WEN Yimin, LI Fang. Collaborative recommendation for scenic spots based on multi-aspect ratings [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2016, 46(6): 54-61.
[11] LIN Yaojin, ZHANG Jia, LIN Menglei, WANG Juan. A method of collaborative filtering recommendation based on fuzzy information entropy [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2016, 46(5): 13-20.
[12] HUANG Dan, WANG Zhihai, LIU Haiyang. A local collaborative filtering algorithm based on ranking recommendation tasks [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2016, 46(5): 29-36.
[13] HOU Yan, YANG Meng. Highly efficient algorithm for tracking explicit surface to process complex topological events [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2016, 46(4): 15-20.
[14] WU Huimin, WU Jingli. An improved cycle basis algorithm for haplotyping a diploid individual [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2016, 46(4): 9-14.
[15] MENG Lingheng, DING Shifei. Depth perceptual model based on the single image [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2016, 46(3): 37-43.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
[1] WANG Su-yu,<\sup>,AI Xing<\sup>,ZHAO Jun<\sup>,LI Zuo-li<\sup>,LIU Zeng-wen<\sup> . Milling force prediction model for highspeed end milling 3Cr2Mo steel[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(1): 1 -5 .
[2] LI Kan . Empolder and implement of the embedded weld control system[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2008, 38(4): 37 -41 .
[3] LI Liang, LUO Qiming, CHEN Enhong. Graph-based ranking model for object-level search
[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2009, 39(1): 15 -21 .
[4] CHEN Rui, LI Hongwei, TIAN Jing. The relationship between the number of magnetic poles and the bearing capacity of radial magnetic bearing[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2018, 48(2): 81 -85 .
[5] LI Ke,LIU Chang-chun,LI Tong-lei . Medical registration approach using improved maximization of mutual information[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(2): 107 -110 .
[6] JI Tao,GAO Xu/sup>,SUN Tong-jing,XUE Yong-duan/sup>,XU Bing-yin/sup> . Characteristic analysis of fault generated traveling waves in 10 Kv automatic blocking and continuous power transmission lines[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(2): 111 -116 .
[7] . [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2009, 39(1): 27 -32 .
[8] QIN Tong, SUN Fengrong*, WANG Limei, WANG Qinghao, LI Xincai. 3D surface reconstruction using the shape based interpolation guided by maximal discs[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2010, 40(3): 1 -5 .
[9] SUN Guohua, WU Yaohua, LI Wei. The effect of excise tax control strategy on the supply chain system performance[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2009, 39(1): 63 -68 .
[10] SUN Weiwei， WANG Yuzhen. Finite gain stabilization of singlemachine infinite bus system subject to saturation[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2009, 39(1): 69 -76 .
Copyright 2018 © Editorial office of Journal of Shandong University (Engineering Science)
Supported by Beijing Magtech Co.Ltd