On Mining XML Structures Based on Statistics

We propose an approach to dynamically generate database schemas for well-formed XML data. Our approach controls the number of tables to be divided based on statistics of XML so that the total cost of processing queries is reduced. We devise schemas appropriate for complex data such as text formatting and child elements with the small maximum number of occurrences in order to reduce the number of tables. To this end, we define three functions NULL expectation, Large Leaf Fields, and Large Child Fields for controlling the tables to be divided. We evaluated typical XML queries over the generated schemas and normalized schemas and measured and compared both of the costs. Through this, we successfully validated our approach.