Holistically Twig Matching in Probabilistic XML

Traditional databases manage only deterministic information, but now many applications that use databases involve uncertain data. For example, it is infeasible for a sensor database to contain only the exact value of each sensor at all points in time. The uncertainty is inherent in these systems due to measurement and sampling errors, and resource limitations. This paper aims at the query processing algorithm of twig patterns on probabilistic XML documents. The existing algorithms evaluate twig patterns in a traversal way. The main shortcoming of this way is scanning the whole probabilistic XML document to get the final results. In this paper, we first represent a probabilistic XML document in the form of probabilistic tag streams and then match them in a holistic way. Extensive experiments are conducted and show that the proposed holistic way has the higher performance than the traversal way.