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Automatically Generated DAML Markup for Semistructured Documents

  • William Krueger
  • Jonathan Nilsson
  • Tim Oates
  • Timothy Finin
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2926)

Abstract

The semantic web is becoming a realizable technology due to the efforts of researchers to develop semantic markup languages such as the DARPA Agent Markup Language (DAML). A major problem that faces the semantic web community is that most information sources on the web today lack semantic markup. To fully realize the potential of the semantic web, we must find a way to automatically upgrade information sources with semantic markup. We have developed a system based on the STALKER algorithm that automatically generates DAML markup for a set of documents based on previously seen labeled training documents. Our rule-learning approach to semantic markup is highly effective when dealing with semistructured documents.

Keywords

Full System Average Recall Training Document Forward Rule Ontology Element 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Ciravegna, F.: (LP)2, an Adaptive Algorithm for Information Extraction from Web-related Texts. In: Proceedings of the IJCAI-2001 Workshop on Adaptive Text Extraction and Mining held in conjunction with 17th International Joint Conference on Artificial Intelligence, IJCAI (2001)Google Scholar
  2. 2.
    Cost, R.S., Finin, T., Joshi, A., Peng, Y., Nicholas, C., Soboroff, I., Chen, H., Kagal, L., Perich, F., Zou, Y., Tolia, S.: ITtalks: A Case Study in the Semantic Web and DAML+OIL. IEEE Intelligent Systems 17(1), 40–47 (2002)CrossRefGoogle Scholar
  3. 3.
    Hendler, J.: Agents and the Semantic Web. IEEE Intelligent Systems 16(2), 30–37 (2001)CrossRefGoogle Scholar
  4. 4.
    Hendler, J., McGuinness, D.L.: The Darpa Agent Markup Language. IEEE Intelligent Systems 15(6), 67–73 (2000)CrossRefGoogle Scholar
  5. 5.
    Knoblock, C.A., Lerman, K., Minton, S., Muslea, I.: Accurately and reliably extracting data from the web: A machine learning approach. Data Engineering BulletinGoogle Scholar
  6. 6.
    Muslea, I., Minton, S., Knoblock, C.: Hierarchical wrapper induction for semistructured information sources. Journal of Autonomous Agents and Multi-Agent Systems (2001)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • William Krueger
    • 1
  • Jonathan Nilsson
    • 1
  • Tim Oates
    • 1
  • Timothy Finin
    • 1
  1. 1.CSEE DepartmentUMBCBaltimoreUSA

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