Title :
Developments in Partitioning XML Documents by Content and Structure Based on Combining Multiple Clusterings
Author :
Costa, Gianni ; Ortale, Riccardo
Author_Institution :
ICAR, Rende, Italy
Abstract :
The combination of multiple clusterings for partitioning XML documents is proposed as a promising method, aimed to decompose the inherently difficult problem of catching structural and content relationships within an XML corpus into a number of simpler subproblems. To verify the validity of such an intuition, a new technique for partitioning XML documents is presented, in which conventional clustering techniques operating on flattened representations of individual aspects of the XML documents (that also include some rare patterns) are used to partition the available XML corpus. The effectiveness of the devised technique is revealed by a comparative empirical evaluation on benchmark XML corpora.
Keywords :
XML; document handling; pattern clustering; XML corpus; XML document partitioning; clustering technique; document content; document structure; multiple clustering combination; Electronic publishing; Encyclopedias; Internet; Vectors; Vegetation; XML;
Conference_Titel :
Tools with Artificial Intelligence (ICTAI), 2013 IEEE 25th International Conference on
Conference_Location :
Herndon, VA
Print_ISBN :
978-1-4799-2971-9
DOI :
10.1109/ICTAI.2013.77