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Granulating XML information

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Wybrane pełne teksty z tego czasopisma
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Języki publikacji
EN
Abstrakty
EN
The eXtensible Mark-up Lanquage (XML) is the standard mark-up languqge for representating, exchanging and publishing information on the Web. The XML data model, called Infoset, represents XML documents as multi-sorted graphs, including nodes belonging to a variety of types. XML-based formats are increasingly used as languages for interoperability and agents'communication on the Internet, raising the need for techniques capable to extract and organize heterogeneous XML messages and data while tolerating variations in their internal structure. This paper presents a technique for organizing well-formed XML information items around user pronided graph patterns. Our approach is based on a graph granulation technique that allows agents to exttact XML data at different levels of detail, using XML graphs' edges as a hint to semantic relation between nodes. The design and implementation of a software tool for XML data granulation are also discussed.
Rocznik
Strony
411--431
Opis fizyczny
Bibliogr. 24 poz., rys., tab.
Twórcy
autor
  • Università di Milano, Dipartimento di Tecnologie dell’Informazione
autor
  • LaTrobe University, Computer Science Department
Bibliografia
  • [1] J. Baldwin and T. Martin: Fuzzy Modelling in an Intelligent Data Browser. Proc. FUZZ-IEEE, Yokohama, Japan, (1995), 1171-1176.
  • [2] G. Bordogna, D. Lucarella and G. Pasi: A Fuzzy Object Oriented Data Model. IEEE Int. Conf. on Fuzzy Systems, 1 (1994), 313-317.
  • [3] P. Bosc: On the Primitivity of the Division of Fuzzy Relations. Soft Computing, 2(2), (1998).
  • [4] B. Bouchon-Meunier, M. Rifqi and S. Bothorel: Towards General Measures of Comparison of Objects. Fuzzy Sets and Systems, 84 (1996).
  • [5] D. Box, A. Lam and D. Skinnard: XML: Beyond Markup. DevelopMentor Series, Addison-Wesley, 2001.
  • [6] S. Ceri and A. Bonifati: A Comparison of Four XML Query Languages. SIGMOD Record, 29(1), (2000).
  • [7] R. Cohen, G. Di Battista, A. Kanevsky and R. Tamassia: Reinventing the Wheel: An Optimal Data Structure for Connectivity Queries. Proc. ACM-TOC Symp. on the Theory of Computing, S.Diego, USA, (1993).
  • [8] S. Comai, E. Damiani, R. Posenato and L. Tanca: A Schema-Based Approach to Modeling and Querying WWW Data. In H. Cristiansen, (Ed)., Proc. of Flexible Query Answering Systems, Roskilde, Denmark, Lecture Notes in Artificial Intelligence 1495 Springer, (1998).
  • [9] E. Damiani And L. Tanca: Blind Queries to XML Data. Proc. DEXA, London, UK, (2000). Lecture Notes in Computer Science, 1873 Springer, (2000), 345-356.
  • [10] E. Damiani, L. Tanca and F. Arcelli Fontana: Fuzzy XML Queries via Context-based Choice of Aggregations. Kybernetika, 4(16), (2000).
  • [11] D. Dubois, F. Esteva, P. Garcia, L. Godo, R. Lopez De Mantaras and H. Prade: Fuzzy Set Modelling in Case-Based Reasoning. Int. J. of Intelligent Systems, 13(1), (1998).
  • [12] D. Dubois, H. Prade and F. Sedes: Fuzzy Logic Techniques in Multimedia Database Querying: A Preliminary Investigations of the Potentials. In R. Meersman, Z. Tari and S. Stevens, (Eds), Database Semantics: Semantic Issues in Multimedia Systems, Kluwer Academic Publisher, 1999.
  • [13] S. Gold and A. Rangajaran: A Graduated Assignment Algorithm for Graph Matching. IEEE Trans. on on Pattern Analysis amd Machine Intelligence, 18(2), (1996), 104-118.
  • [14] S. Haustein and S. Luedecke: Towards Information Agent Interoperability. In M. Klusch, L. Kerschberg (Eds), Cooperative Information Agents, Lecture Notes in Artificial Intelligence 1860 (2000), 208-219.
  • [15] R. Khosla, I. Sethi and E. Damiani: Intelligent Multimedia Multi-Agent Systems. Kluwer Academic Publisher, 2001.
  • [16] G. Klir and T. Folger: Fuzzy Sets, Uncertainty and Information. Prentice Hall, 1988.
  • [17] J. Mordeson and P. Nair: Fuzzy Graphs and Hypergraphs. Studies in Fuzziness and Soft Computing, Physica-Verlag, 2000.
  • [18] K. Nomot: A Document Retrieval System Based on Citations Using Fuzzy Graphs. Fuzzy Sets and Systems, 38 (1990), 207-222.
  • [19] W. Pedrycz and G. Vukovich: Intelligent Agents in Granular Worlds. In V. Loia, S. Sessa, (Eds), Soft Computing Agents, Studies in Fuzziness and Soft Computing, Physica-Verlag, 2002.
  • [20] J.G. Stell: Granulation for Graphs. In C. Freksa and D.M. Mark (Eds), Spatial Information Theory. Cognitive and Computational Foundations of Geographic Information Science. Lecture Notes in Computer Science, 1661 Springer, (1999), 417-432.
  • [21] W3C. Extensible Stylesheet Language (XSL) Version 1.0. October 2000. http://www.w3C.org/TR/xsl/
  • [22] W3C. Extensible Markup Language (XML) 1.0. W3C Recommendation, Feb. 1998. http://www.w3C.org/TR/REC-xml/
  • [23] W3C. Document Object Model Level 3 (DOM) W3C Working Draft, Jan. 2002 http://www.w3.org/TR/2002/WD-DOM-Level-3-Core-20020114/
  • [24] W3C. XSL Transformations (XSLT) Version 1.0 W3C Recommendation 16 November 1999. http://www.w3.org/TR/xslt
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BSW3-0003-0005
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