XML data clustering: An overview
Algergawy, Alsayed, Nayak, Richi, & Mesiti, Marco (2011) XML data clustering: An overview. ACM Computing Surveys (CSUR), 43(4).
In the last few years we have observed a proliferation of approaches for clustering XML docu-ments and schemas based on their structure and content. The presence of such a huge amount of approaches is due to the different applications requiring the XML data to be clustered. These applications need data in the form of similar contents, tags, paths, structures and semantics. In this paper, we first outline the application contexts in which clustering is useful, then we survey approaches so far proposed relying on the abstract representation of data (instances or schema), on the identified similarity measure, and on the clustering algorithm. This presentation leads to draw a taxonomy in which the current approaches can be classified and compared. We aim at introducing an integrated view that is useful when comparing XML data clustering approaches, when developing a new clustering algorithm, and when implementing an XML clustering compo-nent. Finally, the paper moves into the description of future trends and research issues that still need to be faced.
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|Item Type:||Journal Article|
|Keywords:||XML, Clustering, XCLS, Tree Similarity, Schema Matching|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Pattern Recognition and Data Mining (080109)|
|Divisions:||Past > Schools > Computer Science|
Past > QUT Faculties & Divisions > Faculty of Science and Technology
|Copyright Owner:||Copyright 2011 ACM|
|Copyright Statement:||Copyright ACM, . This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in [ACM Computing Surveys], [VOL 43, ISS 4, (2011)] [10.1145/1978802.1978804]|
|Deposited On:||25 Jan 2012 10:57|
|Last Modified:||25 Jan 2012 13:32|
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