JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE) ›› 2016, Vol. 46 ›› Issue (5): 13-20.doi: 10.6040/j.issn.1672-3961.1.2016.165

Previous Articles     Next Articles

A method of collaborative filtering recommendation based on fuzzy information entropy

LIN Yaojin, ZHANG Jia, LIN Menglei, WANG Juan   

  1. School of Computer Science, Minnan Normal University, Zhangzhou 363000, Fujian, China
  • Received:2016-03-01 Online:2016-10-20 Published:2016-03-01

PDF (PC)

972

Abstract: The performance of collaborative filtering was restricted by the sparsity of rating data. To solve this problem, a novel similarity measure based on fuzzy mutual information was proposed. First, the definition of user fuzzy information entropy was given to reflect the uncertainty degree of rating preference. Then, the fuzzy mutual information between users was introduced to measure the similarity degree between users. Finally, the fuzzy information entropy based on similarity measure method was designed to calculate the similarity between users by considering not only the fuzzy mutual information between users but also user fuzzy information entropy. Experimental results on two benchmark data sets showed that the fuzzy information entropy based similarity measure method could reduce the influence of the data sparsity, and the recommendation performance of systems had significant improvements.

Key words: data sparsity, fuzzy information entropy, fuzzy mutual information, collaborative filtering, similarity

CLC Number: 

  • TP391
[1] ADOMAVICIUS G, TUZHILIN A. Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions[J]. IEEE Transactions on Knowledge and Data Engineering, 2005, 17(6):734-749.
[2] PAPAGELIS M, PLEXOUSAKIS D, KUTSURAS T. Alleviating the sparsity problem of collaborative filtering using trust inferences[C] //Proc of the 3rd International Conference on Trust Management. Berlin, Germany: Springer, 2005:224-239.
[3] SHI Yue, LARSON M, HANJALIC A. Collaborative filtering beyond the user-item matrix: a survey of the state of the art and future challenges[J]. ACM Computing Surveys, 2014, 47(1):3:1-3:45.
[4] RESNICK P, IACOVOU N, SUCHAK M, et al. GroupLens: an open architecture for collaborative filtering of netnews[C] //Proc of the ACM Conference on Computer Supported Cooperative Work. New York, USA: ACM, 1994:175-186.
[5] BREESE J S, HECKERMAN D, KADIE C. Empirical analysis of predictive algorithms for collaborative filtering[C] //Proc of the 14th Conference on Uncertainty in Artificial Intelligence. San Francisco, USA: Morgan Kaufmann Publishers Inc, 1998:43-52.
[6] 吴湖,王永吉,王哲,等.两阶段联合聚类协同过滤算法[J].软件学报,2010,21(5):1042-1054. WU Hu, WANG Yongji, WANG Zhe, et al. Two-phase collaborative filtering algorithm based on co-clustering[J]. Journal of Software, 2010, 21(5):1042-1054.
[7] 杨兴耀,于炯,吐尔根·伊布拉音,等.融合奇异性和扩展过程的协同过滤模型[J].软件学报,2013,24(8):1868-1884. YANG Xingyao, YU Jiong, IBRAHIM Turgun, et al. Collaborative filtering model fusing singularity and diffusion process[J]. Journal of Software, 2013, 24(8): 1868-1884.
[8] 林耀进,胡学钢,李慧宗.基于用户群体影响的协同过滤推荐算法[J].情报学报,2013,32(3):299-305. LIN Yaojin, HU Xuegang, LI Huizong. Collaborative filtering recommendation algorithm based on user group influence[J]. Journal of the China Society for Scientific and Technical Information, 2013, 32(3):299-305.
[9] 张佳,林耀进,林梦雷,等.基于目标用户近邻修正的协同过滤算法[J].模式识别与人工智能,2015,28(9):802-810. ZHANG Jia, LIN Yaojin, LIN Menglei, et al. Target users neighbors modification based collaborative filtering[J]. Pattern Recognition and Artificial Intelligence, 2015, 28(9): 802-810.
[10] SARWAR B, KARPIS G, KONSTAN J, et al. Item-based collaborative filtering recommendation algorithms[C] //Proc of the 10th International Conference on World Wide Web. New York, USA: ACM, 2001: 285-295.
[11] KALELI C. An entropy-based neighbor selection approach for collaborative filtering[J]. Knowledge-Based Systems, 2014, 56: 273-280.
[12] JAMALI M, ESTER M. TrustWalker: a random walk model for combining trust-based and item-based recommendation[C] //Proc of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, USA: ACM, 2009: 397-406.
[13] ZHANG J, LIN Y, LIN M, et al. An effective collaborative filtering algorithm based on user preference clustering[J]. Applied Intelligence, 2016, 45(2):230-240.
[14] 黄创光,印鉴,汪静,等.不确定近邻的协同过滤推荐算法[J].计算机学报,2010,33(8):1369-1377. HUANG Chuangguang, YIN Jian, WANG Jing, et al. Uncertain neighbors collaborative filtering recommendation algorithm[J]. Chinese Journal of Computers, 2010, 33(8):1369-1377.
[15] 张佳,林耀进,林梦雷,等.基于信息熵的协同过滤算法[J].山东大学学报(工学版),2016,46(2):43-50. ZHANG Jia, LIN Yaojin, LIN Menglei, et al. Entropy-based collaborative filtering algorithm[J]. Journal of Shandong University(Engineering Science), 2016, 46(2):43-50.
[16] BOBADILLA J, HERNANDO A, ORTEGA F, et al. Collaborative filtering based on significances[J]. Information Sciences, 2012, 185(1):1-17.
[1] WANG Xufeng, ZHOU Di, ZHANG Fenglei, SONG Xuemeng, LIU Meng. Multi-granularity alignment network for image-text matching [J]. Journal of Shandong University(Engineering Science), 2025, 55(4): 29-39.
[2] Gang HU, Lemeng WANG, Zhiyu LU, Qin WANG, Xiang XU. Importance identification method based on multi-order neighborhood hierarchical association contribution of nodes [J]. Journal of Shandong University(Engineering Science), 2024, 54(1): 1-10.
[3] Longmao HU,Xuegang HU. Identification of the same product feature based on multi-dimension similarity and sentiment word expansion [J]. Journal of Shandong University(Engineering Science), 2020, 50(2): 50-59.
[4] Wenkai ZHANG,Ke YU,Xiaofei WU. Entity recommendation based on normalized similarity measure of meta graph in heterogeneous information network [J]. Journal of Shandong University(Engineering Science), 2020, 50(2): 66-75.
[5] Shengnan ZHANG,Lei WANG,Chunhong CHANG,Benli HAO. Image denoising based on 3D shearlet transform and BM4D [J]. Journal of Shandong University(Engineering Science), 2020, 50(2): 83-90.
[6] Delei CHEN, Cheng WANG, Jianwei CHEN, Yiyin WU. GRU-based collaborative filtering recommendation algorithm with active learning [J]. Journal of Shandong University(Engineering Science), 2020, 50(1): 21-27.
[7] Yingda LI,Zongxia XIE. Support vector regression algorithm based on kernel similarity reduced strategy [J]. Journal of Shandong University(Engineering Science), 2019, 49(3): 8-14.
[8] Yun HU,Shu ZHANG,Hui LI,Kankan SHE,Jun SHI. Recommendation algorithm based on trust network reconfiguration [J]. Journal of Shandong University(Engineering Science), 2019, 49(2): 42-46.
[9] Zhongwei ZHANG,Hongyan MEI,Jun ZHOU,Huiping JIA. A rule extraction method based on multi-objective co-evolutionarygenetic algorithm [J]. Journal of Shandong University(Engineering Science), 2019, 49(2): 122-130.
[10] LIN Jianghao, ZHOU Yongmei, YANG Aimin, CHEN Jin. Building of domain sentiment lexicon based on word2vec [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2018, 48(3): 40-47.
[11] CUI Xiaosong, WANG Ying, MENG Jia, ZOU Li. Online business self-evaluation system based on linguistic-valued similarity reasoning [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2018, 48(1): 1-7.
[12] SONG Yang, ZHONG Maiying. Fault isolability analysis based on improved distance similarity [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(5): 103-109.
[13] PANG Renming, WANG Bo, YE Hao, ZHANG Haifeng, LI Mingliang. Clustering of blast furnace historical data based on PCA similarity factor and spectral clustering [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(5): 143-149.
[14] LI Zhenwei, CUI Guozhong, GUO Congzhou, YU Changhao. Blind image restoration using alternating direction method of multipliers [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(4): 14-18.
[15] HAO Chongqing, WANG Zhihong. Classification and analysis of epileptic EEG based on complex networks [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2017, 47(3): 8-15.
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] KONG Xiang-zhen,LIU Yan-jun,WANG Yong,ZHAO Xiu-hua . Compensation and simulation for the deadband of the pneumatic proportional valve[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(1): 99 -102 .
[4] 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 .
[5] 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 .
[6] 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 .
[7] 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 .
[8] . [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2009, 39(1): 27 -32 .
[9] WANG Li-ju,HUANG Qi-cheng,WANG Zhao-xu . [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(6): 51 -56 .
[10] SUN Dianzhu, ZHU Changzhi, LI Yanrui. [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2009, 39(1): 84 -86 .
Copyright 2018 © Editorial office of Journal of Shandong University (Engineering Science)
Supported by Beijing Magtech Co.Ltd