Computer Science ›› 2019, Vol. 46 ›› Issue (11A): 163-166.

• Data Science • Previous Articles     Next Articles

Research on Relationship Between Bipartite Network Recommendation Algorithm and Collaborative Filtering Algorithm

ZHOU Bo   

  1. (China Institute of Atomic Energy,Beijing 102413,China)
  • Online:2019-11-10 Published:2019-11-20

Abstract: This paper introduced the basic principle of collaborative filtering algorithm and bipartite network recommendation algorithm,and proposed the general bipartite network recommendation algorithm.The internal relationship between the two algorithms was analyzed.The results show that collaborative filtering algorithm is a special case of the bipartite network recommendation algorithm,and bipartite network algorithm is proved to perforem better than collaborative recommendation algorithm.This research systematizes and unifies the bipartite recommendation algorithm theory and promotes the further development of recommendation algorithm.

Key words: Collaborative filtering, Bipartite network, Recommendation algorithm

CLC Number: 

  • TP391
[1]裴中佑.基于随机游走的推荐技术研究及应用[D].成都:西南交通大学,2014.
[2]MASSA P,AVESANI P.Trust-Aware Collaborative Filtering for Recommender Systems[M]∥On the Move to Meaningful Internet Systems 2004:CoopIS,DOA,and ODBASE.Springer Berlin Heidelberg,2004:492-508.
[3]李聪,梁昌勇.基于n序访问解析逻辑的协同过滤冷启动消除方法[J].系统工程理论与实践,2012(7):1537-1545.
[4]李小浩.协同过滤推荐算法稀疏性与可扩展性问题研究[D].重庆:重庆大学,2015.
[5]孙小华.协同过滤系统的稀疏性与冷启动问题研究[D].杭州:浙江大学,2005.
[6]徐键.协同过滤中数据稀疏问题与推荐实时性的研究[D].兰州:兰州大学,2016.
[7]TAO Z,JIE R,MATUˇS M,et al.Bipartite network projection and personal recommendation[J].Physical Review E,2007,76(4):70-80.
[8]周波,杨朝峰.发送者和接受者能力的二分网络推荐算法研究[J].情报工程,2016,2(2):71-80.
[9]何平凡.基于排序学习的Top-N推荐算法研究[D].北京:北京理工大学,2016.
[10]赵向宇.Top-N协同过滤推荐技术研究[D].北京:北京理工大学,2014.
[11]陈嘉颖,于炯,杨兴耀,等.基于复杂网络节点重要性的链路预测算法[J].计算机应用,2016(12):3251-3255,3268.
[12]荣莉莉,郭天柱,王建伟.复杂网络节点中心性[J].上海理工大学学报,2008,30(3):227-230.
[13]姚尊强,尚可可,许小可.加权网络的常用统计量[J].上海理工大学学报,2012,34(1):18-26.
[1] WANG Rui-ping, JIA Zhen, LIU Chang, CHEN Ze-wei, LI Tian-rui. Deep Interest Factorization Machine Network Based on DeepFM [J]. Computer Science, 2021, 48(1): 226-232.
[2] MA Li-bo, QIN Xiao-lin. Topic-Location-Category Aware Point-of-interest Recommendation [J]. Computer Science, 2020, 47(9): 81-87.
[3] LIU Jun-liang, LI Xiao-guang. Techniques for Recommendation System:A Survey [J]. Computer Science, 2020, 47(7): 47-55.
[4] LUO Jia-lei and MENG Li-min. Signal Timing Scheme Recommendation Algorithm Based on Intersection Similarity [J]. Computer Science, 2020, 47(6A): 66-69.
[5] MA Hai-Jiang. Recommendation Algorithm Based on Convolutional Neural Network and Constrained Probability Matrix Factorization [J]. Computer Science, 2020, 47(6A): 540-545.
[6] ZHU Lei, HU Qin-han, ZHAO Lei, YANG Ji-wen. Collaborative Filtering Algorithm Based on Rating Preference and Item Attributes [J]. Computer Science, 2020, 47(4): 67-73.
[7] ZHAO Nan, PI Wen-chao, XU Chang-qiao. Video Recommendation Algorithm for Multidimensional Feature Analysis and Filtering [J]. Computer Science, 2020, 47(4): 103-107.
[8] FENG Chen-jiao,LIANG Ji-ye,SONG Peng,WANG Zhi-qiang. New Similarity Measure Based on Extremely Rating Behavior [J]. Computer Science, 2020, 47(2): 31-36.
[9] WU Lei,YUE Feng,WANG Han-ru,WANG Gang. Academic Paper Recommendation Method Combined with Researcher Tag [J]. Computer Science, 2020, 47(2): 51-57.
[10] HUANG Chao-ran, GAN Yong-shi. Balance Between Preference and Universality Based on Explicit Feedback Collaborative Filtering [J]. Computer Science, 2020, 47(11A): 471-473.
[11] ZHOU Bo. Bipartite Network Recommendation Algorithm Based on Semantic Model [J]. Computer Science, 2020, 47(11A): 482-485.
[12] KANG Yan, BU Rong-jing, LI Hao, YANG Bing, ZHANG Ya-chuan, CHEN Tie. Neural Collaborative Filtering Based on Enhanced-attention Mechanism [J]. Computer Science, 2020, 47(10): 114-120.
[13] WANG Han, XIA Hong-bin. Collaborative Filtering Recommendation Algorithm Mixing LDA Model and List-wise Model [J]. Computer Science, 2019, 46(9): 216-222.
[14] DENG Cun-bin, YU Hui-qun, FAN Gui-sheng. Integrating Dynamic Collaborative Filtering and Deep Learning for Recommendation [J]. Computer Science, 2019, 46(8): 28-34.
[15] ZHANG Yan-hong, ZHANG Chun-guang, ZHOU Xiang-zhen, WANG Yi-ou. Diverse Video Recommender Algorithm Based on Multi-property Fuzzy Aggregate of Items [J]. Computer Science, 2019, 46(8): 78-83.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
[1] LEI Li-hui and WANG Jing. Parallelization of LTL Model Checking Based on Possibility Measure[J]. Computer Science, 2018, 45(4): 71 -75 .
[2] SUN Qi, JIN Yan, HE Kun and XU Ling-xuan. Hybrid Evolutionary Algorithm for Solving Mixed Capacitated General Routing Problem[J]. Computer Science, 2018, 45(4): 76 -82 .
[3] ZHANG Jia-nan and XIAO Ming-yu. Approximation Algorithm for Weighted Mixed Domination Problem[J]. Computer Science, 2018, 45(4): 83 -88 .
[4] WU Jian-hui, HUANG Zhong-xiang, LI Wu, WU Jian-hui, PENG Xin and ZHANG Sheng. Robustness Optimization of Sequence Decision in Urban Road Construction[J]. Computer Science, 2018, 45(4): 89 -93 .
[5] SHI Wen-jun, WU Ji-gang and LUO Yu-chun. Fast and Efficient Scheduling Algorithms for Mobile Cloud Offloading[J]. Computer Science, 2018, 45(4): 94 -99 .
[6] ZHOU Yan-ping and YE Qiao-lin. L1-norm Distance Based Least Squares Twin Support Vector Machine[J]. Computer Science, 2018, 45(4): 100 -105 .
[7] LIU Bo-yi, TANG Xiang-yan and CHENG Jie-ren. Recognition Method for Corn Borer Based on Templates Matching in Muliple Growth Periods[J]. Computer Science, 2018, 45(4): 106 -111 .
[8] GENG Hai-jun, SHI Xin-gang, WANG Zhi-liang, YIN Xia and YIN Shao-ping. Energy-efficient Intra-domain Routing Algorithm Based on Directed Acyclic Graph[J]. Computer Science, 2018, 45(4): 112 -116 .
[9] CUI Qiong, LI Jian-hua, WANG Hong and NAN Ming-li. Resilience Analysis Model of Networked Command Information System Based on Node Repairability[J]. Computer Science, 2018, 45(4): 117 -121 .
[10] WANG Zhen-chao, HOU Huan-huan and LIAN Rui. Path Optimization Scheme for Restraining Degree of Disorder in CMT[J]. Computer Science, 2018, 45(4): 122 -125 .