XCLS: A fast and effective clustering algorithm for heterogenous XML documents

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3918 LNAI, Issue , 2006, Pages 292-302

  Nayak, Richi ^a   Xu, Sumei ^a  

^a QUEENSLAND UNIVERSITY OF TECHNOLOGY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATION THEORY; COMPUTER SCIENCE; DATA PROCESSING; INFORMATION RETRIEVAL; XML;

CLUSTERING ALGORITHM; LEVEL STRUCTURE; STRUCTURAL INFORMATION;

ALGORITHMS;

EID: 33745775475     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11731139_35     Document Type: Conference Paper

References (15)

1. Bertino, E., Guerrini, G. & Mesiti, M. (2004). A Matching Algorithm for Measuring the Structural Similarity between an XML Document and a DTD and its applications. Information Systems, 29(1): 23-46.
2. Boag S. Chamberlin D, Fernández M, Florescu D, Robie J and Siméon J. "XQuery 1.0: An XML Query Language" W3C Working Draft, September, 2005. http://www.w3.org/TR/ 2005/WD-xquery-20050915/
3. Flesca, S., Manco, G., Masciari, E., Pontieri, L., & Pugliese, A. (2005). Fast Detection of XML Structural Similarities. IEEE Transaction on Knowledge and Data Engineering, Vol 7 (2), pp 160-175.
4. st, 2005, from http://www.hitsw.com/ products_services/whitepapers/ integrating_xml_rdb/integrating_xml_white_paper.pdf.
5. Jain, A. K., Murty, M. N., & Flynn, P. J. (1999). Data Clustering: A Review. ACM Computing Surveys (CSUR), 31(3), 264-323.
6. Leung, H.-p., Chung, F.-l., & Chan, S. C.-f. (2005). On the use of hierarchical information in sequential mining-based XML document similarity computation. Knowledge and Information Systems, 7(4),pp 476-498.
7. Nayak R and Iryadi W (2006). XMine: A methodology for mining XML structure. To appear in The Eighth Asia Pacific Web Conference. January 2006, China.
8. Nayak R & Xia, F. B. (2004). "Automatic integration of heterogenous XML-schemas", Proceedings of the International Conferences on Information Integration and Web-based Applications & Services. Jakarta, Indonesia, Sec 27-29, pp. 427-437.
9. Nayak, R., Witt, R., and Tonev, A. (2002) Data Mining and XML documents, International Conference on Internet Computing, USA.
10. Xylem L. (2001). Xylem: A dynamic Warehouse for XML data of the Web," IDEAS'01, pp3-7, 2001.
11. Yergeau, F, Bray T, Paoli J, Sperberg-McQueen, C M and Maler E. (2004). Extensible Markup Language (XML) 1.0 (Third Edition) W3C Recommendation, February 2004, http://www.w3.org/TR/2004/REC-XML-20040204/
12. Ying Y, Guan X and You J. (2002), CLOPE: A Fast and effective clustering algorithm for transactional data,
13. Wang, K., Xu, C. (1999), Clustering Transactions Using Large Items, in the proceedings of ACM CIKM-99, Kansas, Missouri.
14. Zhang, K., & Shasha, D. (1989). Simple Fast Algorithms for the Editing Distance Between Trees and Related Problems. SIAM Journal Computing, 18(6), 1245-1262.
15. Zhao, Y., & Karypis, G. (2002). Evaluation of Hierarchical Clustering Algorithms for Document Datasets. The 2002 ACM CIKM, USA.