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XEdge: clustering homogeneous and heterogeneous XML documents using edge summaries
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Source Symposium on Applied Computing archive
Proceedings of the 2008 ACM symposium on Applied computing table of contents
Fortaleza, Ceara, Brazil
SESSION: Information access and retrieval table of contents
Pages 1081-1088  
Year of Publication: 2008
ISBN:978-1-59593-753-7
Authors
Panagiotis Antonellis  University of Patras, Greece, Rio, Patras
Christos Makris  University of Patras, Greece, Rio, Patras
Nikos Tsirakis  University of Patras, Greece, Rio, Patras
Sponsor
SIGAPP: ACM Special Interest Group on Applied Computing
Publisher
ACM  New York, NY, USA
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ABSTRACT

In this paper we propose a unified clustering algorithm for both homogeneous and heterogeneous XML documents. Depending on the type of the XML documents, the proposed algorithm modifies its distance metric in order to properly adapt to the special structural characteristics of homogeneous and heterogeneous XML documents. We compare the quality of the formed clusters with those of one of the latest XML clustering algorithms and show that our algorithm outperforms it in the case of both homogeneous and heterogeneous XML documents.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Abiteboul, S., Buneman, P. and Suciu, D. Data on the Web. Morgan Kaufmann, 2000.
 
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Nayak, R. and Xu, S. XCLS: A Fast and Effective Clustering Algorithm for Heterogeneous XML Documents. In Proceedings of the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD '06) (The Singapore, April 9--12, 2006). 2006, pp. 292--302.
 
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Tagarelli, A. and Greco, S. Toward Semantic XML Clustering. In Proceedings of the 2006 Siam Conference on Data Mining (SDM '06) (Maryland, USA, 2006). 2006, pp. 188--199.

Collaborative Colleagues:
Panagiotis Antonellis: colleagues
Christos Makris: colleagues
Nikos Tsirakis: colleagues