On multiple query optimization in data mining

被引：0

作者：

Wojciechowski, M ^{[1
]}

Zakrzewicz, M ^{[1
]}

机构：

[1] Poznan Tech Univ, Inst Comp Sci, PL-60965 Poznan, Poland

来源：

ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PROCEEDINGS | 2005年 / 3518卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Traditional multiple query optimization methods focus on identifying common subexpressions in sets of relational queries and on constructing their global execution plans. In this paper we consider the problem of optimizing sets of data mining queries submitted to a Knowledge Discovery Management System. We describe the problem of data mining query scheduling and we introduce a new algorithm called CCAgglomerative to schedule data mining queries for frequent itemset discovery.

引用

页码：696 / 701

页数：6

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