XML data can be represented by a tree or graph structure and XML query processing requires the information of structural relationships among nodes. The basic structural relationships are parent-child and ancestor-descendant, and finding all occurrences of these basic structural relationships in an XML data is clearly a core operation in XML query processing. Several node labeling schemes have been suggested to support the determination of ancestor-descendant or parent-child structural relationships simply by comparing the labels of nodes. However, the previous node labeling schemes have some disadvantages, such as a large number of nodes that need to be relabeled in the case of an insertion of XML data, huge space requirements for node labels, and inefficient processing of structural joins.
Additionally there is a growing interest in the data model and query processing for probabilistic XML data. There are many potential applications of probabilistic data, and the XML data model is suitable to represent hierarchical information and data uncertainty of different levels naturally. However, the previously proposed probabilistic XML data models and query processing techniques separate finding data matches and evaluating the probabilities of results. Therefore, they should repeatedly access the data and need to get full data of paths given in queries to calculate the probabilities of results.
In order to support efficient XML query and update processing, we propose the nested tree structure that eliminates the disadvantages and takes advantage of the previous node labeling schemes. The nested tree structure makes it possible to use the dynamic interval-based labeling scheme, which supports XML data updates with almost no node relabeling as well as efficient structural join processing.
In addition, we suggest an extended interval-based labeling scheme for the probabilistic XML data tree and an efficient query processing procedure using the labeling scheme. Against p...