Integrating Frequent Itemsets Mining with Relational Database

摘要：

Frequent itemsets mining is becoming increasingly important since the size of databases grows even larger. Currently database systems are dominated by relational database. However the performance of SQL based data mining is known to fall behind specialized implementation and expensive mining tools being on sale. In this paper we analyzed a famous frequent itemsets discovery algorithms FP-growth,and propose a new implementation approach called DBFP-Growth to create disk-based FP-tree based on ORACLE PL/SQL, it can execute faster than using SQL directly. Also presents a novel SQL-based method DRRW, which can remove duplicate records from database without temp table generation.

关键词： Database Frequent itemset Data mining

作者: Qiu Yong

作者单位: Shandong Institute of Business and Technology,YanTai 264005 China

会议类型: 国际会议

会议名称: 第八届国际电子测量与仪器学术会议(Proceedings of 2007 8th International Conference on Electronic Measurement & Instruments)

会议地点: 西安

会议语种:英文

在线出版日期: 2007-08-16（万方平台首次上网日期，不代表论文的发表时间）