期刊文献+

数据挖掘技术在网络教学资源建设中的应用

下载PDF
导出
摘要 数据挖掘技术是促进网络教学资源发展的重要技术 ,本文对数据挖掘技术作一简要概述 ,介绍了数据挖掘的分析方法、数据挖掘的过程 ,提出数据挖掘工具 。
出处 《现代远距离教育》 北大核心 2004年第2期41-43,共3页 Modern Distance Education
  • 相关文献

参考文献2

二级参考文献14

  • 1Brin, S., Motwani, R., and Silvemtein, C. (1997a). Beyond Market Baskets: Generalizing Association Rules to Correlations. In Proceedings of the ACM SIGMOD International Conference on Management of Data (ACM SIGMOD 97), Pages 265-276. 被引量:1
  • 2Brin, S., Motwani, R., Ullman, J. D., and Tsur, S. (1997b). Dynamic Itemset Counting and Implication Rules for Market Basket Data. In Proceedings of the ACM SIGMOD International Conference on Management of Data (ACM SIGMOD 97), Pages 265-276. 被引量:1
  • 3English, L P. (1999). Improving Data Warehouse and Business Information Quality: Methods for Reducing Costs and Increasing profits. John Wiley & Sons, New York, USA. 被引量:1
  • 4Fayyad, U., Piatetsky-Shapiro, G., and Smyth, P. (1996). The KDD Process for Extracting Useful Knowledge from Volumes of Data. Communications of the ACM, 39(11):27-34. 被引量:1
  • 5Gersten, W., Wirth, R., and Arndt, D. (2000). Predictive Modeling in Automotive Direct Marketing: Tools, Experiences and Open Issues. In Proceedings of the 6th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD 00), Pages 398-406, Boston, MA USA. 被引量:1
  • 6Han, J., Pei, J., and Yin, Y. (2000). Mining Frequent Patterns without Candidate Generation. In Pmceedings of the 2000 ACM-SIGMOD International Confenerence on Management of Data, Dallas, Texas, USA. 被引量:1
  • 7Handley, S., Langley, P., and Rauscher, F. A. (1998). Learn ing to Predict the Duration of an Automobile Trip. In Proceedings of 1998 International Conference on KDD and Data Mining (KDD98), Pages 219-223, New York City, USA. 被引量:1
  • 8Hipp, J., Guntzer, U., and Grimmer, U. (2001). Integrating Association Rule Mining Algorithms with Relational Database Systems.In Proceedings of the International Conference on Enterprise Information Systems (ICEIS2001),Set'ubal, Portuga. 被引量:1
  • 9Hipp, .1., G untzer, U., and Nakhaeizadeh, G. (2000a). Algo Rithms for Association Rule Mining - a General Survey and Comparison. SIGKDD Explorations, 2(1):58--64. 被引量:1
  • 10Hipp, J., G untzer, U., and Nakhaeizadeh, G. (2000b). Mining Association Rules: Deriving a Superior Algorithm by Analysing Today's Approaches. In Proceedings of the 4th European Symposium on Principles of Data Mining and Knowledge Discovery (PKDD 00), Pages 159-168, Lyon, France. 被引量:1

共引文献9

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部