Titlebook: Knowledge Discovery from XML Documents; First International Richi Nayak,Mohammed J. Zaki Conference proceedings 2006 Springer-Verlag Berli

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0302-9743 10th Paci?c-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2006. The workshop provided an important forum for the dissemination and exchange of new ideas and research related to XML data discovery and retrieval. The eXtensible Markup Language (XML) has become a standard language for

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Discovering Multi Terms and Co-hyponymy from XHTML Documents with XTREEMch can be obtained from traditional HTML documents) Web Documents..The XTREEM (Xhtml TREE Mining) method uses structural information, the mark-up in Web content, as indicators of term boundaries and for co-hyponymy relations.

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Machine Learning Models: Combining Evidence of Similarity for XML Schema Matchingthe SMO for the high precision and recall, we increase the reliability of the final matching results. The precision is therefore enhanced (e.g., with data sets used by Cupid and suggested by the author of LSD, our precision is respectively 13.05% and 31.55% higher than COMA and Cupid on average).

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Information Retrieval from Distributed Semistructured Documents Using Metadata Interfaceg nodes with the same label that often exist in semistructured data. The system uses Quilt as its XML query language. An experiment is reported over three local semistructured documents: ‘thesis’, ‘reports’, and ‘journal’ documents with ‘article’ global schema. The prototype was developed under Windows system with Java and JavaCC.

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