An efficient algorithm for twig joins in probabilistic XML
Bo Ning, Guanyu Li, Xin Zhou, Yan Qing Zhao · 2010
In the real world, uncertain data exist exoterically, as in many area of application, it is impossible to express data with uncertainty of one hundred percents. The uncertainty is inherent in these systems due to measurement and sampling errors, and resource limitations. The flexibility of XML data model allows a more natural representation of uncertain data compared with the relational model. The matching of a twig pattern against probabilistic XML data is an essential problem in the query processing of probabilistic XML. Many typical algorithms of twig join in XML of certainty can not be used or be adjusted to process against probabilistic XML, because of the new characteristics of uncertain XML data, such as the distribution nodes and probabilistic values. In this paper, we propose an algorithm for twig joins against probabilistic XML which is based on a new prefix encoding scheme. Experiments have been conducted to study the performance of the proposed algorithm.