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From Tables to Frames

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The Semantic Web – ISWC 2004 (ISWC 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3298))

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Abstract

Turning the current Web into a Semantic Web requires automatic approaches for annotation of existing data since manual approaches will not scale in general. We here present an approach for automatic generation of F-Logic frames out of tables which subsequently supports the automatic population of ontologies from table-like structures. The approach consists of a methodology, an accompanying implementation and a thorough evaluation. It is based on a grounded cognitive table model which is stepwise instantiated by our methodology.

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References

  1. Chen, H., Tsai, S., Tsai, J.: Mining tables from large scale HTML texts. In: Proc. of the 18th Int. Conf. on Computational Linguistics (COLING), pp. 166–172 (2000)

    Google Scholar 

  2. Codd, E.A.: A relational model for large shared databanks. Communications of the ACM 13(6), 377–387 (1970)

    Article  MATH  Google Scholar 

  3. Cohen, W., Ravikumar, P., Fienberg, S.: A comparison of string distance metrics for namematching tasks. In: Proceedings of the IIWeb Workshop at the IJCAI 2003 conference (2003)

    Google Scholar 

  4. Decker, S., Erdmann, M., Fensel, D., Studer, R.: Ontobroker: Ontology Based Access to Distributed and Semi-Structured Information. In: Meersman, R., et al. (eds.) Database Semantics: Semantic Issues in Multimedia Systems, pp. 351–369. Kluwer, Dordrecht (1999)

    Google Scholar 

  5. Fellbaum, C.: WordNet, an electronic lexical database. MIT Press, Cambridge (1998)

    MATH  Google Scholar 

  6. Handschuh, S., Staab, S. (eds.): Annotation in the Semantic Web. IOS Press, Amsterdam (2003)

    Google Scholar 

  7. Hurst, M.: Layout and language: Beyond simple text for information interaction - modelling the table. In: Proc. of the 2nd Int. Conf. on Multimodal Interfaces, Hong Kong, (1999)

    Google Scholar 

  8. Hurst, M.: The Interpretation of Tables in Texts. PhD thesis, University of Edinburgh (2000)

    Google Scholar 

  9. Kifer, M., Lausen, G., Wu, J.: Logical foundations of object-oriented and frame-based languages. Journal of the ACM 42, 741–843 (1995)

    Article  MATH  MathSciNet  Google Scholar 

  10. Lerman, K., Minton, S., Knoblock, C.: Wrapper maintenance:Amachine learning approach. J. of Artificial Intelligence Research 18, 149–181 (2003)

    MATH  Google Scholar 

  11. Maedche, A.: Ontology Learning for the Semantic Web. Kluwer Academic Publishers, Dordrecht (2002)

    MATH  Google Scholar 

  12. McCallum, A., Freitag, D., Pereira, F.: Maximum entropy markov models for information extraction and segmentation. In: Proceedings of the ICML 2000, pp. 591–598 (2000)

    Google Scholar 

  13. Ng, H.T., Kim, C.Y., Koo, J.L.T.: Learning to recognize tables in free text. In: Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics, pp. 443–450 (1999)

    Google Scholar 

  14. Pinto, D., Croft, W., Branstein, M., Coleman, R., King, M., Li, W., Wei, X.: Quasm:A system for question answering using semi-structured data. In: Proceedings of the Joint Conference on Digital Libraries (JCDL 2002), pp. 46–55 (2002)

    Google Scholar 

  15. Pinto, D., McCallum, A., Wei, X., Croft, W.B.: Table extraction using conditional random fields. In: Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval, pp. 235–242. ACM Press, New York (2003)

    Chapter  Google Scholar 

  16. Wang, H.L., Wu, S.H., Wang, I.C., Sung, C.L., Hsu, W.L., Shih, W.K.: Semantic Search on Internet Tabular Information Extraction for Answering Queries. In: Proc. of the Ninth Int. Conf. on Information and Knowledge Management, Washington DC, pp. 243–249 (2000)

    Google Scholar 

  17. Wang, X.: Tabular Abstraction, Editing and Formatting. PhD thesis, U. of Waterloo (1996)

    Google Scholar 

  18. Zanibbi, R., Blostein, D., Cordy, J.R.: A survey of table recognition: Models, observations, transformations, and inferences. In: International Journal of Document Analysis and Recognition (to appear)

    Google Scholar 

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© 2004 Springer-Verlag Berlin Heidelberg

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Pivk, A., Cimiano, P., Sure, Y. (2004). From Tables to Frames. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds) The Semantic Web – ISWC 2004. ISWC 2004. Lecture Notes in Computer Science, vol 3298. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30475-3_13

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  • DOI: https://doi.org/10.1007/978-3-540-30475-3_13

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23798-3

  • Online ISBN: 978-3-540-30475-3

  • eBook Packages: Springer Book Archive

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