Association rule mining is one of most popular data analysis methods that can discover associations within data. Association rule mining algorithms have been applied to various datasets, due to their practical usefulness. Little attention has been paid, however, on how to apply the association minin
Mining predecessor–successor rules from DAG data
✍ Scribed by Yen-Liang Chen; Chih-Hao Ye; Shin-Yi Wu
- Publisher
- John Wiley and Sons
- Year
- 2006
- Tongue
- English
- Weight
- 402 KB
- Volume
- 21
- Category
- Article
- ISSN
- 0884-8173
No coin nor oath required. For personal study only.
✦ Synopsis
Data mining extracts implicit, previously unknown, and potentially useful information from databases. Many approaches have been proposed to extract information, and one of the most important ones is finding association rules. Although a large amount of research has been devoted to this subject, none of it finds association rules from directed acyclic graph ~DAG! data. Without such a mining method, the hidden knowledge, if any, cannot be discovered from the databases storing DAG data such as family genealogy profiles, product structures, XML documents, task precedence relations, and course structures. In this article, we define a new kind of association rule in DAG databases called the predecessor-successor rule, where a node x is a predecessor of another node y if we can find a path in DAG where x appears before y. The predecessorsuccessor rules enable us to observe how the characteristics of the predecessors influence the successors. An approach containing four stages is proposed to discover the predecessor-successor rules.
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