Researcb on Social Network Collaborative Filtering Based E-commerce Recommending

Chunhua Ju; Fuguang Bao; Chonghuan Xu

doi:10.3969／j.issn.1000-0801.2014.09.011

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Researcb on Social Network Collaborative Filtering Based E-commerce Recommending

research and development | 更新时间：2024-06-05

- Researcb on Social Network Collaborative Filtering Based E-commerce Recommending
- Telecommunications Science Vol. 30, Issue 9, Pages: 82-86(2014)
- 作者机构：
  
  1. 浙江工商大学现代商贸研究中心杭州310018
  2. 浙江工商大学计算机与信息工程学院杭州310018
  3. 浙江工商大学工商管理学院杭州310018
- 作者简介：
- 基金信息：
- DOI：10.3969／j.issn.1000-0801.2014.09.011
  CLC：
- Published Online：2014-09，
  
  Published：20 September 2014
- 稿件说明：
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Chunhua Ju, Fuguang Bao, Chonghuan Xu. Researcb on Social Network Collaborative Filtering Based E-commerce Recommending[J]. Telecommunications science, 2014, 30(9): 82-86.
DOI：

Chunhua Ju, Fuguang Bao, Chonghuan Xu. Researcb on Social Network Collaborative Filtering Based E-commerce Recommending[J]. Telecommunications science, 2014, 30(9): 82-86. DOI： 10.3969／j.issn.1000-0801.2014.09.011.

摘要

随着社会网络关系的不断复杂化，商品是否推荐成功，除了基于商品本身的特征外，还受社会网络关系的影响。很多用户更加信任来自朋友的推荐，而非机器通过单因素计算出来的推荐结果。因此，设计了一个融入社会网络关系的电子商务推荐系统。其中，构建了社会网络关系强度、兴趣偏好强度和商品流行性与声望强度3个关键因子，每个一级因子又由若干个二级因子构成。实验结果验证了社会网络关系会对其中成员的网购等网络行为产生影响，构建的基于社会网络的电子商务推荐策略的效果比其他单因素推荐策略好且稳定，具有很好的实际应用效果。

Abstract

With the development of the social network relation

whether the recommendation is successful

is not only depending on the characteristics of goods

but also influenced by social network relationship. Many users more trust from their friends'recommendation

rather than the machine recommended by single factor calculated results. Therefore

an E-commerce recommending system based on social network collaborative filtering was proposed. In the system

the crucial factors of social network relation intensity

interest preference intensity and production popularity with reputation intensity were set.And each first-level factor was composed of some second-level factors.Experimental results verify that social network relationships will affect users shopping behaviors and so on. In addition

the recommendation method based on social network is superior to other approaches and has better application effect.

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Keywords

references

中国互联网络信息中心 . 第33次中国互联网络发展状况统计报告 . http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/201403/t20140305_46240.htm http://www.cnnic.net.cn/hlwfzyj/hlwxzbg/hlwtjbg/201403/t20140305_46240.htm , 2014

Ni Y , Xie L , Liu Q Z . Minimizing the expected complete influence time of asocial network . Information Sciences 2010 , 180 ( 1 ): 2514 ～ 2527

Klein A , Bhagat P . E-commerce: evidence on a new virtual commerce platform . Journal of Business Research , 2010 , 4 ( 1 ): 107 ～ 124

Liang T P , Ho Y T , Li Y W , et al . What drives social commerce: the role of social support and relationship quality . International Journal of Electronic Commerce , 2011 , 16 ( 1 ): 69 ～ 90

赵华 , 林政 , 方艾 , 等 . 一种基于知识树的推荐算法及其在移动电子商务上的应用 . 电信科学 2011 , 27 ( 6 )

陶彩霞 , 谢晓军 , 陈康 , 等 . 基于云计算的移动互联网大数据用户行为分析引擎设计 . 电信科学 2013 , 29 ( 3 ): 30 ～ 35

Li Y , Lu L , Feng L X . A hybrid collaborative filtering method for multiple-interests and multiple-content recommendation in E-commerce . Expert Systems with Applications , 2005 , 28 ( 1 ): 67 ～ 77

Jeong B , Lee J , Cho H . Improving memory-based collaborative filtering via similarity updating and prediction modulation . Information Sciences , 2010 , 180 ( 1 ): 602 ～ 612

琚春华 , 鲍福光 . 基于情境和主体特征融入性的多维度个性化推荐模型研究 . 通信学报 2012 , 33 ( 9A ): 17 ～ 27

Pan W K , Yang Q . Transfer learning in heterogeneous collaborative filtering domains . Artificial Intelligence , 2013 , 197 ( 1 ): 39 ～ 55

张海燕 , 孟祥武 . 基于社会标签的推荐系统研究 . 情报理论与实践 2012 , 35 ( 5 ): 103 ～ 106

孟祥武 , 胡勋 , 王立才 , 等 . 移动推荐系统及其应用 . 软件学报 2013 , 24 ( 1 ): 91 ～ 108

Ranganathan C , Ganapathy S . Key dimensions of business-to-consumer web sites . Information＆Management , 2002 , 39 ( 6 ): 457 ～ 465

张佩云 , 陈恩红 , 黄波 . 基于社会网络面向个性化需求的可信服务推荐 . 通信学报 2013 ( 12 ): 49 ～ 59

Hsia T L , Wu J H , Li Y E . The E-commerce value matrix and use case model:a goal-driven methodology for eliciting B2C application requirements . Information＆Management , 2008 , 45 ( 5 ): 321 ～ 330

DeMeo P , Nocera A , Terracina G , et al . Recommendation of similar users,resources and social networks in a social internetworking scenario . Information Sciences , 2010 , 181 ( 1 ): 1285 ～ 1305

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