Discovering Pattern-Based Dynamic Structures from Versions of Unordered XML Documents
Abstract
Existing works on XML data mining deal with snapshot XML data only, while XML data is dynamic in real applications. in this paper, we discover knowledge from XML data by taking account its dynamic nature. We present a novel approach to extract pattern-Based dynamic structures from versions of unordered XML documents. with the proposed dynamic metrics, the pattern-Based dynamic structures are expected to summarize and predict interesting change trends of certain structures based on their past behaviors. Two types of pattern-Based dynamic structures, increasing dynamic structure and decreasing dynamic structure are considered. with our proposed data model, SMH-Tree, an algorithm for mining such pattern-Based dynamic structures with only two scans of the XML sequence is presented. Experimental results show that the proposed algorithm can extract the pattern-Based dynamic structures efficiently with good scalability. © Springer-Verlag Berlin Heidelberg 2004.
Recommended Citation
Q. Zhao et al., "Discovering Pattern-Based Dynamic Structures from Versions of Unordered XML Documents," Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3181, pp. 77 - 86, Springer, Jan 2004.
The definitive version is available at https://doi.org/10.1007/978-3-540-30076-2_8
Department(s)
Computer Science
International Standard Book Number (ISBN)
978-354022937-7
International Standard Serial Number (ISSN)
1611-3349; 0302-9743
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Springer, All rights reserved.
Publication Date
01 Jan 2004
