document: Xproj : a framework for projected structural clustering of xml documents XML has become a popular method of data representation both on the web and in databases in recent years . One of the reasons for the popularity of XML has been its ability to encode structural information about data records . However , this structural characteristic of data sets also makes it a challenging problem for a variety of data mining problems . One such problem is that of clustering , in which the structural aspects of the data result in a high implicit dimensionality of the data representation . As a result , it becomes more difficult to cluster the data in a meaningful way . In this paper , we propose an effective clustering algorithm for XML data which uses substructures of the documents in order to gain insights about the important underlying structures . We propose new ways of using multiple sub-structuralinformation in XML documents to evaluate the quality of intermediate cluster solutions , and guide the algorithms to a final solution which reflects the true structural behavior in individual partitions . We test the algorithm on a variety of real and synthetic data sets .
doc_bio_tags: O O O O O O O B O B O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O