In the last few years we have observed a proliferation of approaches for clustering XML docu-udments and schemas based on their structure and content. The presence of such a huge amountudof approaches is due to the different applications requiring the XML data to be clustered. Theseudapplications need data in the form of similar contents, tags, paths, structures and semantics. Inudthis paper, we first outline the application contexts in which clustering is useful, then we surveyudapproaches so far proposed relying on the abstract representation of data (instances or schema),udon the identified similarity measure, and on the clustering algorithm. This presentation leads touddraw a taxonomy in which the current approaches can be classified and compared. We aim atudintroducing an integrated view that is useful when comparing XML data clustering approaches,udwhen developing a new clustering algorithm, and when implementing an XML clustering compo-udnent. Finally, the paper moves into the description of future trends and research issues that stilludneed to be faced.
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