Clustering XML documents using structural summaries

Dalamagas, T; Cheng, T; Winkel, K-J; Sellis, T

dc.contributor.author	Dalamagas, T	en
dc.contributor.author	Cheng, T	en
dc.contributor.author	Winkel, K-J	en
dc.contributor.author	Sellis, T	en
dc.date.accessioned	2014-03-01T01:20:00Z
dc.date.available	2014-03-01T01:20:00Z
dc.date.issued	2004	en
dc.identifier.issn	0302-9743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/15803
dc.subject	Cluster Algorithm	en
dc.subject	Structural Similarity	en
dc.subject	Tree Structure	en
dc.subject	Xml Document	en
dc.subject.classification	Computer Science, Theory & Methods	en
dc.title	Clustering XML documents using structural summaries	en
heal.type	journalArticle	en
heal.identifier.primary	10.1007/978-3-540-30192-9_54	en
heal.identifier.secondary	http://dx.doi.org/10.1007/978-3-540-30192-9_54	en
heal.language	English	en
heal.publicationDate	2004	en
heal.abstract	This work presents a methodology for grouping structurally similar XML documents using clustering algorithms. Modeling XML documents with tree-like structures, we face the 'clustering XML documents by structure' problem as a 'tree clustering' problem, exploiting distances that estimate the similarity between those trees in terms of the hierarchical relationships of their nodes. We suggest the usage of tree structural summaries to improve the performance of the distance calculation and at the same time to maintain or even improve its quality. Experimental results are provided using a prototype testbed. © Springer-Verlag 2004.	en
heal.publisher	SPRINGER-VERLAG BERLIN	en
heal.journalName	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en
heal.bookName	LECTURE NOTES IN COMPUTER SCIENCE	en
dc.identifier.doi	10.1007/978-3-540-30192-9_54	en
dc.identifier.isi	ISI:000226132200054	en
dc.identifier.volume	3268	en
dc.identifier.spage	547	en
dc.identifier.epage	556	en