Fast and effective clustering of XML data using structural information

Knowledge and Information Systems

Volumn 14, Issue 2, 2008, Pages 197-215

  Nayak, Richi ^a  

^a QUEENSLAND UNIVERSITY OF TECHNOLOGY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

CLUSTER ANALYSIS; ECONOMIC AND SOCIAL EFFECTS; NATURAL LANGUAGE PROCESSING SYSTEMS; SEMANTICS; XML;

DOCUMENTS CLUSTERING; EXPERIMENTAL ANALYSIS; GLOBAL CRITERION FUNCTION; HETEROGENEOUS DOCUMENTS; INCREMENTAL CLUSTERING ALGORITHM; SEMANTIC SIMILARITY; STRUCTURAL INFORMATION; STRUCTURAL SIMILARITY;

CLUSTERING ALGORITHMS;

EID: 38649116960     PISSN: 02191377     EISSN: 02193116     Source Type: Journal    
DOI: 10.1007/s10115-007-0080-8     Document Type: Conference Paper

References (26)

1. The Wisconisn's XML data bank. Accessed from: http://www.cs.wisc.edu/ hiagara/data.html. Cited Sept 2004
2. The XML data repository. Accessed from: http://www.cs.washington.edu/ research/xmldatasets/. Cited Sept 2004
3. INEX (2005) Document mining track. Accessed from: http://inex.is.informatik.uni-duisburg.de/2005/
4. wCluto: Web Interface for CLustering TOolKit (2003) AHcessed from: http://cluto.ccgb.umn.edu/cgi-bin/wCluto/wCluto.cgi, on: July 25, 2005
5. 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. Inf Syst 29(1):23-46
6. Boag S et al (2005) XQuery 1.0: An XML Query Language. Accessed from: http://www.w3.org/TR/2005/WD-xquery-20050915/, on: September 2005
7. Fellbaum C (1998) WordNet: An electronic lexical database. MIT Press, Cambridge
8. Flesca S et al (2005) Fast Detection of XML structural similarities. IEEE Trans Know Data Eng 7(2): 160-175
9. Giumchiglia F, Yatskevich M (2004) Element level semantic matching. In: Meaning coordination and negotiation workshop at ISWC
10. Guardalben G (2004) Integrating XML and relational database technologies: A position paHer. Accessed from: http://www.hitsw.com/ products_services/whitepapers/integrating_xml_rdb/ integrating_xml_white_paper.pdf, on: May 1, 2005
11. Jain AK, Murty MN, Flynn PJ (1999) Data clustering: A review. ACM Comput Surv (CSUR) 31(3): 264-323
12. Lee LM et al (2002) XClust: Clustering XML schemas for effective integration. In: 11th ACM international conference on information and knowledge management (CIKM'02), November 2002, Virginia
13. Leung H-P, Chung F-l, Chan SC-F (2005) On the use of hierarchical information in sequential mining-based XML document similarity computation. Know Inf Syst 7(4):476-498
14. Madhavan J, Bernstein PA, Rahm E (2001) Generic schema matching with cupid. In: 27th VLDB. Roma, Italy
15. Meier W (2002) eXist: An open source native XML database. In: Web, Web-services, and database systems. LNCS, vol. 2593, pp 169-183
16. Nayak R, Zaki MJ (eds) (2006) Proceedings of the 2006 Workshop on "Knowledge Discovery from XML documents", vol. 3915. LNCS
17. Nayak R, Iryadi W (2006) XMine: A methodology for mining XML structure. In Asia Pacific Web Conference, ASWeb 2006, January, China
18. Nayak R, Witt R, Tonev A (2002) Data Mining and XML documents. In The 2002 International Workshop on the Web and Database (WebDB 2002). June 24-27, 2002
19. Nierman A, Jagadish HV (2002) Evaluating structural similarity in XML documents. In 5th international conference on computational science (ICCS'05). December, Wisconsin, USA
20. Rice SV, Bunke H, Nartker TA (1997) Classes of cost functions for string edit distance. Algorithmica 18(2):271-280
21. Wang K, Xu C (1999) Clustering transactions using large items. In: ACM CIKM. Kansas, Missouri
22. Xylem L (2001) Xylem: A dynamic warehouse for XML data of the Web. In IDEAS, pp 3-7
23. Yergeau F et al (2004) Extensible markup language (XML) 1.0, (3rd edn.) W3C Recommendation. Accessed from: http://www.w3.org/TR/2004/ REC-XML-20040204/, on: February 2004
24. Ying Y, Guan X, You J (2002) CLOPE: A fast and effective clustering algorithm for transactional data. In: KDD
25. Zhang K, Shasha D (1989) Simple fast algorithms for the editing distance between trees and related problems. SIAM J Comput 18(6):1245-1262
26. Zhao Y, Karypis G (2001) Criterion functions for document clustering: Experiments and analysis. Department of Computer Science, University of Minnesota, Minneapolis