Mining approximate keys based on reasoning from XML data

Abstract

Keys are very important for data management. Due to the hierarchical and flexible structure of XML, mining keys from XML data is a more complex and difficult task than from relational databases. In this paper, we study mining approximate keys from XML data, and define the support and confidence of a key expression based on the number of null values on key paths. In the mining process, inference rules are used to derive new keys. Through the two-phase reasoning, a target set of approximate keys and its reduced set are obtained. Our research conducted experiments over ten benchmark XML datasets from XMark and four files in the UW XML Repository. The results show that the approach is feasible and efficient, with which effective keys in various XML data can be discovered. © Springer-Verlag 2013.