期刊文献+

关联规则与直接模糊聚类算法在个性化推荐中的应用

Association Rules and Fuzzy Clustering Algorithm used in Personal Recommendation
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摘要 随着Internet技术的发展,网络教育已成为一种非常流行和有效的教学媒体。通过Web挖掘应用于网络教育,根据用户的兴趣和爱好为其定制个性化推荐内容,并以此进行个性化推荐,是目前校园网站建设的关键内容之一。 Association rules and clustering are two important topics in the datamining, this paper gives a t methods of datamining,tries to integrate the two presents a method which can effectively reduce the number of data. The results show the algorithm can improve the data mining performance and reduce the redundancy rules.
作者 国伟 王浩
机构地区 合肥工业大学
出处 《电脑开发与应用》 2007年第10期44-46,共3页 Computer Development & Applications
关键词 数据挖掘 关联规则 聚类分析 联合挖掘 datamining association rules direct fuzzy clustering combined Mining
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参考文献5

  • 1Aggarwal C, Yu P. Data mining techniques for personalizaticn [J]. IEEE Data Engineering Bulletin, 2000,23(1) :4-9.
  • 2陈耿,朱玉全,杨鹤标,陆介平,宋余庆,孙志挥.关联规则挖掘中若干关键技术的研究[J].计算机研究与发展,2005,42(10):1785-1789. 被引量:62
  • 3范明 孟小峰.数据挖掘概念与技术[M].北京:机械工业出版社,2003.152-157.
  • 4高新波.模糊聚类分析及其应用[M].西安:西安电子科技大学出版社,1994.
  • 5Jeffery P. Database Access weith Visual Basic [M]. Beijing: PublishingHouse of Electronics Industry, 1999.

二级参考文献12

  • 1R. Agrawal, T. Imielinski, A. Swami. Mining association rules between sets of items in large databases. ACM SIGMOD Int'l Conf. Management of Data, Washington, D. C., 1993.
  • 2Han J, Kamber. MData Mining: Concepts and Techniques.Beijing: High Education Press, 2001.
  • 3B. Goethals. Survey of frequent pattern mining. Helsinki Institute for Information Technology, Technical Report, 2003.
  • 4R. Agrawal, R. Srikant. Fast algorithm for mining association rules. The 20th Int'l Conf. VLDB, Santiago, Chile, 1994.
  • 5M. Houtsma, A. Swami. Set-oriented mining for association rules in relational databases. In: Yu P., Chen A, eds. Proc. Int'l Conf. Data Engineering. Los Alamitos, CA: IEEE Computer Society Press, 1995. 25~33.
  • 6A. Savasere, E. Omiecinski, S. Navathe. An efficient algorithm for mining association rules. The 21st Int' l Conf. VLDB, Zurich,Switzerland, 1995.
  • 7J. Han, Y. Fu. Discovery of multiple-level association rules from large databases. The 21st Int'l Conf. VLDB, Zurich,Switzerland, 1995.
  • 8R. Bayardo. Efficiently mining long patterns from databases. In:L. M. Haas, A. Tiwary, eds. Proc. ACM SIGMOD Int'l Conf.Management of Data. New York: ACM Press, 1998. 85~93.
  • 9Lin, Dao-I, Z. M. Kedem. Pincer-Search: A new algorithm for discovering the maximum frequent set. In: H. J. Schek, F.Saltor, I. Ramos et al. eds. Proc. 6th European Conf.Extending Database Technology. Berlin: Springer-Veriag, 1998.105~119.
  • 10D.W. Cheung, J. Han, V. T. Ng, et al. Maintenance of discovered association rules in large databases: An incremental updating technique. The 12th Int'l Conf. Data Engineering, New Orleans, Louisiana, 1996.

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