Hierarchical clustering of XML documents focused on structural components
Clustering XML documents by structure is the task of grouping them by common structural components. Hitherto, this has been accomplished by looking at the occurrence of one preestablished type of structural components in the structures of the XML documents. However, the a-priori chosen structural components may not be the most appropriate for effective clustering. Moreover, it is likely that the resulting clusters exhibit a certain extent of inner structural inhomogeneity, because of uncaught differences in the structures of the XML documents, due to further neglected forms of structural components. To overcome these limitations, a new hierarchical approach is proposed, that allows to consider (if necessary) multiple forms of structural components to isolate structurally-homogeneous clusters of XML documents. At each level of the resulting hierarchy, clusters are divided by considering some type of structural components (unaddressed at the preceding levels), that still differentiate the structures of the XML documents. Each cluster in the hierarchy is summarized through a novel technique, that provides a clear and differentiated understanding of its structural properties. A comparative evaluation over both real and synthetic XML data proves that the devised approach outperforms established competitors in effectiveness and scalability. Cluster summarization is also shown to be very representative.
data mining semi-structured data and xml xml clustering xml transactional representation xml cluster summarization and representative