• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>International Conference on Electronic Business（ICEB 2004) vol.2; 20041205-09; Beijing(CN) >A Personalized Commodities Recommendation Procedure and Algorithm Based on Association Rule Mining
【24h】

A Personalized Commodities Recommendation Procedure and Algorithm Based on Association Rule Mining

机译：基于关联规则挖掘的个性化商品推荐程序和算法

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The double-quick growth of EB has caused commodities overload, where our customers are not longer able to efficiently choose the products adapt to them. In order to overcome the situation that both companies and customers are facing, we present a personalized recommendation, although several recommendation systems which may have some disadvantages have been developed. In this paper, we focus on the association rule mining by EFFICIENT algorithm which can simple discovery rapidly the all association rules without any information loss. The EFFICIENT algorithm which comes of the conventional Aprior algorithm integrates the notions of fast algorithm and predigested algorithm to find the interesting association rules in a given transaction data sets. We believe that the procedure should be accepted, and experiment with real-life databases show that the proposed algorithm is efficient one.
机译：EB的快速增长导致商品超负荷，我们的客户不再能够有效地选择适合他们的产品。为了克服公司和客户都面临的情况，我们提出了个性化的推荐，尽管已经开发了一些可能具有某些缺点的推荐系统。在本文中，我们着重于通过EFFICIENT算法的关联规则挖掘，该算法可以快速简单地发现所有关联规则，而不会造成任何信息丢失。常规Aprior算法中的EFFICIENT算法将快速算法和简化算法的概念结合在一起，以在给定的交易数据集中找到有趣的关联规则。我们认为该程序应被接受，并且通过实际数据库的实验表明，该算法是一种有效的算法。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号