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An effective approach to mine relational patterns and its extensive analysis on multi-relational databases

机译:一种有效的关系模式挖掘方法及其对多关系数据库的广泛分析

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摘要

The real world applications of data mining necessitate more complicated solutions when the data includes large quantity of records in several tables of relational database. One of the possible solutions is multi-relational pattern mining, which is a form of data mining applicable to data in multiple tables. In this paper, we have developed an effective approach to mine relational patterns from multi-relational database. Initially, the multi-relational database is represented using a tree-based data structure without changing their relations. A tree pattern mining algorithm is devised and applied on the constructed tree-based data structure for extracting the frequent relational patterns. Experimentation is carried out on two different databases and the results are compared with the previous approach using number of similar relational patterns generated and the computation time. The comparative analysis shows that the proposed approach is more effective in mining performance and computation time compared to the previous approach.
机译:当数据在关系数据库的多个表中包含大量记录时,数据挖掘的实际应用需要更复杂的解决方案。可能的解决方案之一是多关系模式挖掘,这是一种适用于多个表中数据的数据挖掘形式。在本文中,我们已经开发了一种从多关系数据库挖掘关系模式的有效方法。最初,使用基于树的数据结构表示多关系数据库,而无需更改它们之间的关系。设计了一种树模式挖掘算法,并将其应用于构建的基于树的数据结构中,以提取频繁的关系模式。在两个不同的数据库上进行了实验,并使用生成的相似关系模式的数量和计算时间将结果与以前的方法进行了比较。比较分析表明,与以前的方法相比,该方法在挖掘性能和计算时间上更为有效。

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