An Efficient Bulk Updating Method for Finite Automaton Based XML Filtering Systems

In structure-oriented XML filtering systems, approaches that use event-based parsing techniques and automatons are proved to have sufficiently high performance. Many of these filtering systems are based on Finite Automaton (FA). In this paper, we study the updating techniques for the FA-based filtering engine, which is the most important component of an XML filtering system and propose an efficient bulk updating method which considers common prefixes among the new arriving queries. Experiments show that our method provides significantly better scalability and performance when compared to existing methods.