XML filtering applications are gaining increasing popularity recently. Automata are generally adopted to construct query indexes for evaluating large numbers of XPath queries over XML streams. Usually only shallow data are observed in existing approaches. How to process deep and recursive XML data with low memory limitation efficiently is still a challenging issue. In this paper, we propose HFilter, a Hybrid Finite Automaton (HFA) based stream filtering approach, to solve this problem. We introduce the basic two-tier HFA (lazy DFA tier and NFA tier) first, which realizes data prefix sharing and memory overflow control to improve the filtering throughput. Then an optimized three-tier HFA with an extra pre-expanded DFA tier is put forward, which significantly reduces the restarting cost of HFA after memory overflow. Experiments show that our approaches work more efficiently than existing ones. © 2008 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Sun, W., Qin, Y., Yu, P., Zhang, Z., & He, Z. (2008). HFilter: Hybrid finite automaton based stream filtering for deep and recursive XML data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5181 LNCS, pp. 566–580). https://doi.org/10.1007/978-3-540-85654-2_48
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