Collaborative Recommendation Algorithm of Web Customer Demand Based on Item Factor Analysis
CSTR:
Author:
  • Article
  • | |
  • Metrics
  • |
  • Reference [14]
  • |
  • Related [20]
  • | | |
  • Comments
    Abstract:

    In order to solve the problem that data overload and data sparsity in collaborative filtering recommendation algorithm, the collaborative recommendation algorithm based on item factor analysis is proposed in this paper. The algorithm reduces the dimensions of item vector by use of factor analysis and gets some representative item factors, which are used to regression analysis of target items to forecast the evaluated items. Finally, experiments show that the algorithm is effective, which provides a new way for future recommendation algorithm research.

    Reference
    1 吴湖,王永吉,王哲,等.两阶段联合聚类协同过滤算法.软件学报,2010,21(5):1042?1054.
    2 Sarwar B, Kaypis G, Konstan J, Riedl J. Analysis of Recommendation Algorithms for E-Commerce. Proceedings of the 2nd ACM conference on Electronic commerce. New York: ACM Press, 2000.158?167.
    3 李聪,梁昌勇,马丽.基于邻域最近邻的协同过滤推荐算法. 计算机研究与发展,2008,45(9):1532?1538.
    4 Kaypis G. Evaluation of item-based top-n recommendation algorithms. Proc. of the 10th International Conference on Information and Knowledge Management. New York: ACM Press, 2001.247?254.
    5 Sarwar B, Kaypis G, Konstan J, Riedl J. Item-based collaborative filtering recommendation algorithms. Proc. Of the 10th International Conference on World Wide Web. New York: ACM Press, 2001.285?295.
    6 Sarwar B. Sparsity, scalability and distribution in recommender systems [Ph.D. Thesis]. Minneapolis: University of Minnesota, 2001.
    7 汪静,印鉴,郑利荣,黄创光.基于共同评分和相似性权重的协同过滤推荐算法.计算机科学,2010,37(2):99?103.
    8 Linden G, Smith B, York J. Amazon.com recommendations: item-to-item collaborative filtering. IEEE Internet Computing, 2003,7(1):76?80.
    9 张海鹏,李列彪,李仙等. 基于项目分类预测的协同过滤推荐算法.情报学报,2008,27(2):218?223.
    10 龚瑞君,王佳,戴珺等.基于两阶段聚类的协作过滤推荐算法.郑州大学学报(理学版),2010,42(1):14?16.
    11 李聪,梁昌勇,董珂.基于项目类别相似性的协同过滤推荐算法.合肥工业大学学报(自然科学版),2008,31(3):360?363.
    12 邵伟,袁方,张瑜.融入项目类别信息的协同过滤推荐算法. 数学的实践与认识,2010,40(6):108?112.
    13 赵宏霞,杨皎平,陈宗娇.面向客户需求的神经网络挖掘方法.管理评论,2005,17(11):53?57.
    14 马庆国.管理统计:数据获取、统计原理.SPSS 工具与应用研究.北京:科学出版社,2002.315?326.
    Cited by
    Comments
    Comments
    分享到微博
    Submit
Get Citation

赵宏霞,王新海,杨皎平.基于项目因子分析的Web 客户需求协同推荐算法.计算机系统应用,2011,20(7):188-191,210

Copy
Share
Article Metrics
  • Abstract:2005
  • PDF: 3807
  • HTML: 0
  • Cited by: 0
History
  • Received:November 08,2010
  • Revised:December 05,2010
Article QR Code
You are the first990537Visitors
Copyright: Institute of Software, Chinese Academy of Sciences Beijing ICP No. 05046678-3
Address:4# South Fourth Street, Zhongguancun,Haidian, Beijing,Postal Code:100190
Phone:010-62661041 Fax: Email:csa (a) iscas.ac.cn
Technical Support:Beijing Qinyun Technology Development Co., Ltd.

Beijing Public Network Security No. 11040202500063