DocumentCode
2590510
Title
Tree Reconstruction and Bottom-Up Evaluation of Tree Pattern Queries
Author
Chen, Yangjun ; Chen, Yibin
Author_Institution
Dept. Appl. Comput. Sci., Univ. of Winnipeg, Winnipeg, MB, Canada
fYear
2010
fDate
21-23 April 2010
Firstpage
1
Lastpage
8
Abstract
An XML tree pattern query, represented as a labeled tree, is essentially a complex selection predicate on both structure and content of an XML. Tree pattern matching has been identified as a core operation in querying XML data. However, almost all the proposed algorithms only deal with unordered trees, by which the order of siblings is not considered. In this paper, we discuss a new algorithm for processing ordered tree pattern queries, for which not only the ancestor-descendant and parent-child relationships, but also the order of siblings are significant. The time complexity of the algorithm is bounded by O(|D|·|Q| + |T|·leafQ) and its space overhead is by O(leafT·leafQ), where T stands for a document tree, Q for a tree pattern query and D is a largest data stream associated with a query node q of Q, which contains the database nodes that match the node predicate at q. leafT (leafQ) represents the number of the leaf nodes of T (resp. Q). In addition, the algorithm can be adapted to an indexing environment with XB-trees being used. Experiments have been conducted, which shows that the new algorithm is promising.
Keywords
XML; computational complexity; pattern matching; query processing; tree searching; XML data querying; XML tree pattern query; ancestor-descendant relationship; bottom-up evaluation; data stream; database nodes; document tree; eXtensible Markup Language; indexing environment; labeled tree; leaf nodes; node predicate; parent-child relationship; query node; siblings order; space overhead; time complexity; tree pattern matching; tree reconstruction; Character recognition; Computational efficiency; Computer networks; Handwriting recognition; Inference algorithms; Network topology; Neural networks; Optimization methods; Recurrent neural networks; Wind speed;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Science and Applications (ICISA), 2010 International Conference on
Conference_Location
Seoul
Print_ISBN
978-1-4244-5941-4
Electronic_ISBN
978-1-4244-5943-8
Type
conf
DOI
10.1109/ICISA.2010.5480393
Filename
5480393
Link To Document