adaptability in xml-to-relational mapping strategies
One of the ways how to manage XML documents is to exploit tools and functions offered by (object-)relational database systems. The key aim of such techniques is to find the optimal mapping strategy, i.e. the way the XML data are stored into relations. Currently the most efficient approaches, so-called adaptive methods, search a space of possible mappings and choose the one which suits the given sample data and query workload the most. In the paper we exploit a general heuristic method called Ant Colony Optimization (ACO) to solve the XML-to-relational mapping problem. We also adapt the algorithm so it can be used on a dynamic variant of the problem. The algorithms are evaluated in a set of experiments with a conclusion that the ACO-based algorithms are suitable for the problem and can be even used as a basis of a dynamic mapping mechanism.
xml dynamic adaptation storing xml in databases