Schema matching for transforming structured documents

ABSTRACT

Structured document content reuse is the problem of restructuring and translating data structured under a source schema into an instance of a target schema. A notion closely tied with structured document reuse is that of structure transformations. Schema matching is a critical strep in structured document transformations. Manual matching is expensive and error-prone. It is therefore important to develop techniques to automate the matching process and thus the transformation process. In this paper, we contributed in both understanding the matching problem in the context of structured document transformations and developing matching methods those output serves as the basis for the automatic generation of transformation scripts.

REFERENCES

• 1: Sihem Amer-Yahia , SungRan Cho , Divesh Srivastava, Tree Pattern Relaxation, Proceedings of the 8th International Conference on Extending Database Technology: Advances in Database Technology, p.496-513, March 25-27, 2002
• 2: A. Boukottaya. "Schema matching for structured document transformations", PHD thesis, October 2004.
• 3: A. Budanitsky and G. Hirst. Semantic distance in WordNet. An experimental, application oriented evaluation of five measures, 2003.
• 4: D. Carmel, N. Efraty, G.M. Landau, Y.S. Maarek, and Y. Mass. An Extension of the vector space model for querying XML documents via XML fragments. Second Edition of the XML and IR Workshop, In SIGIR Forum, Volume 36 Number 2, Fall 2002.
• 5: S. Chawathe, H. García-Molina, J. Hammer, K. Ireland, Y. Papakonstantinou, J. Ullman, and J. Widom. The TSIMMIS Project: Integration of heterogeneous information sources. In 16th meeting of the IPSJ, pages 7--18, Tokyo, Japan, 1994.
• 6: AnHai Doan , Pedro Domingos , Alon Y. Halevy, Reconciling schemas of disparate data sources: a machine-learning approach, Proceedings of the 2001 ACM SIGMOD international conference on Management of data, p.509-520, May 21-24, 2001, Santa Barbara, California, United States
• 7: D. W. Embley , D. M. Campbell , Y. S. Jiang , S. W. Liddle , D. W. Lonsdale , Y.---K. Ng , R. D. Smith, Conceptual-model-based data extraction from multiple-record Web pages, Data & Knowledge Engineering, v.31 n.3, p.227-251, Nov. 1999 [doi>10.1016/S0169-023X(99)00027-0]
• 8: Lexical chains as representations of context for the detection and correction of malapropisms. In: Christiane Fellbaum (editor), WordNet: An electronic lexical database, Cambridge, MA: The MIT Press, 1998.
• 9: J. A. Larson , S. B. Navathe , R. Elmasri, A Theory of Attributed Equivalence in Databases with Application to Schema Integration, IEEE Transactions on Software Engineering, v.15 n.4, p.449-463, April 1989 [doi>10.1109/32.16605]
• 10: Mong Li Lee , Liang Huai Yang , Wynne Hsu , Xia Yang, XClust: clustering XML schemas for effective integration, Proceedings of the eleventh international conference on Information and knowledge management, November 04-09, 2002, McLean, Virginia, USA [doi>10.1145/584792.584841]
• 11: Paula Leinonen, Automating XML document structure transformations, Proceedings of the 2003 ACM symposium on Document engineering, November 20-22, 2003, Grenoble, France [doi>10.1145/958220.958226]
• 12: Jayant Madhavan , Philip A. Bernstein , Erhard Rahm, Generic Schema Matching with Cupid, Proceedings of the 27th International Conference on Very Large Data Bases, p.49-58, September 11-14, 2001
• 13: Similarity Flooding: A Versatile Graph Matching Algorithm and Its Application to Schema Matching, Proceedings of the 18th International Conference on Data Engineering, p.117, February 26-March 01, 2002
• 14: George A. Miller, WordNet: a lexical database for English, Communications of the ACM, v.38 n.11, p.39-41, Nov. 1995 [doi>10.1145/219717.219748]
• 15: Emmanuel Pietriga , Jean-Yves Vion-Dury , Vincent Quint, VXT: a visual approach to XML transformations, Proceedings of the 2001 ACM Symposium on Document engineering, November 09-10, 2001, Atlanta, Georgia, USA [doi>10.1145/502187.502189]
• 16: Erhard Rahm , Philip A. Bernstein, A survey of approaches to automatic schema matching, The VLDB Journal — The International Journal on Very Large Data Bases, v.10 n.4, p.334-350, December 2001 [doi>10.1007/s007780100057]
• 17: E. Rahm and P.A. Bernstein. On matching schema automatically. Microsoft Research Publications, 2001. Available at http://www.research.microsoft.com/pubs.
• 18: H. Su, H. Kuno, E.A. Rundensteiner. Automating the transformation of XML Documents. In Proceedings of the ACM Symposium on Document Engineering, 2001.
• 19: X. Tang and F. Tompa. Specifying transformations for structured documents. In Proceedings of 4th International Worshop on Web and Databases (WebDB 2001), pages 67--72. 2001.
• 20: A. Vernet. XML transformation languages. Available at http://www.scdi.org/ avernet/misc/xml-transformation
• 21: Extensible Markup Language (XML) 1.0, W3C Recommendation, 1998. Available at http://www.w3.org/TR/REC-XML
• 22: XSL Transformations (XSLT) 1.0, W3C Recommendation, 1999. Available at http://www.w3.org/TR/1999/REC-xslt-19991116
• 23: XML Schema Part 0: Primer, W3C Recommendation, 2001. Available at http://www.w3.org/TR/2001/REC-xmlschema-0-20010502/
• 24: XML Schema Part 2: Datatypes, W3C Recommendation, 2001. Available at http://www.w3.org/TR/2001/REC-xmlschema-2-20010502/
• 25: XSLWIZ. Available at http://www.induslogic.com/products/xslwiz.html
• 26: Li Xu , David W. Embley, Source discovery and schema mapping for data integration, 2003

INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.7 DOCUMENT AND TEXT PROCESSING
      I.7.2 Document Preparation

General Terms:
Documentation, Languages

Keywords:
document structure transformations, schema matching