XML Data Integration based on Content and Structure Similarity using Keys
Abstract
This paper proposes a technique for approximately matching XML data based on the content and structure by detecting the similarity of subtrees clustered semantically using leaf-node parents. the leaf-node parents are considered as a root of a subtree which is then recursively traversed bottom-up for matching. First, we take advantage of the "key" for matching subtrees which reduces the number of comparisons dramatically. Second, we measure the similarity degree based on data and structures of the two XML documents. the results show that our approach finds much more accurate matches with or without the presence of keys in XML subtrees. Other approaches experience problems with similarity matching thresholds as they either ignore semantic information available or have problems in handling complex XML data. © 2008 Springer Berlin Heidelberg.
Recommended Citation
W. Viyanon et al., "XML Data Integration based on Content and Structure Similarity using Keys," Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5331 LNCS, no. PART 1, pp. 484 - 493, Springer, Dec 2008.
The definitive version is available at https://doi.org/10.1007/978-3-540-88871-0_35
Department(s)
Computer Science
Keywords and Phrases
Clustering; Keys; Similarity; XML
International Standard Book Number (ISBN)
978-354088870-3
International Standard Serial Number (ISSN)
1611-3349; 0302-9743
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Springer, All rights reserved.
Publication Date
31 Dec 2008
