We propose XCCS, which is short for XML Classification by Content and Structure, a new approach for the induction of intelligible classification models for XML data, that are a valuable support for more effective and efficient XML search, retrieval and filtering. The idea behind XCCS is to represent each XML document as a transaction in a space of boolean features, that are informative of its content and structure. Suitable algorithms are developed to learn associative classifiers from the transactional representation of the XML data. XCCS induces very compact classifiers with outperforming effectiveness compared to several established competitors.

A transactional approach to associative XML Classification by Content and Structure

Ritacco E.
Co-primo
2011-01-01

Abstract

We propose XCCS, which is short for XML Classification by Content and Structure, a new approach for the induction of intelligible classification models for XML data, that are a valuable support for more effective and efficient XML search, retrieval and filtering. The idea behind XCCS is to represent each XML document as a transaction in a space of boolean features, that are informative of its content and structure. Suitable algorithms are developed to learn associative classifiers from the transactional representation of the XML data. XCCS induces very compact classifiers with outperforming effectiveness compared to several established competitors.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11390/1248969
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