Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-37487-6_23
Title: Querying semi-structured data with mutual exclusion
Authors: Wu, H.
Tang, R.
Ling, T.W. 
Issue Date: 2013
Citation: Wu, H.,Tang, R.,Ling, T.W. (2013). Querying semi-structured data with mutual exclusion. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 7825 LNCS (PART 1) : 284-298. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-37487-6_23
Abstract: Data analytics applications, content-based collaborative platforms and office applications require the integration and management of current and historical data from heterogeneous sources. XML is a standard data format for information. Thanks to its semi-structured-ness, it is a good candidate data model for the integration and management of heterogeneous content. However, the management of historical and collaboratively created data compels considering extensions of the original XML model to constraint-based, probabilistic and temporal aspects. We consider here an extension of the XML data model with mutual exclusion between nodes for the purpose of the management of versions in XML databases. XML query processing algorithms for ordinary XML data focus on the parent-child, ancestor-descendant, sibling and lowest common ancestor relationships between nodes. In this paper, we extend existing labeling schemes and query processing algorithms for the processing of queries over an extension of the XML data model with mutual exclusion. We focus on structured twig pattern query, and show that the same technique can be applied to keyword queries as well. We empirically evaluate the performance of the proposed techniques. © Springer-Verlag 2013.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/78312
ISBN: 9783642374869
ISSN: 03029743
DOI: 10.1007/978-3-642-37487-6_23
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