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Canadian Conference on Artificial Intelligence

Canadian AI 2010: Advances in Artificial Intelligence pp 416–418Cite as

Semantic Annotation Using Ontology and Bayesian Networks

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Part of the Lecture Notes in Computer Science book series (LNAI,volume 6085)

Abstract

The research presents a semantic annotation framework, named BNOSA. The framework uses ontology to conceptualize a problem domain and uses Bayesian networks to resolve conflicts and to predict missing data. Experiments have been conducted to analyze the performance of the presented semantic annotation framework on different problem domains. The sets of corpuses used in the experiment belong to selling-purchasing websites where product information is entered by ordinary web users.

Keywords

  • Ontology
  • Bayesian Network
  • Semantic Annotation

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  • DOI: 10.1007/978-3-642-13059-5_61
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References

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  3. Yildiz, B., Miksch, S.: OntoX - a method for ontology-driven information extraction. In: Gervasi, O., Gavrilova, M.L. (eds.) ICCSA 2007, Part III. LNCS, vol. 4707, pp. 660–673. Springer, Heidelberg (2007)

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  4. Rajput, Q.N., Haider, S.: Use of Bayesian Network in Information Extraction from Unstructured Data Sources. International Journal of Information Technology 5(4), 207–213 (2009)

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Author information

Authors and Affiliations

  1. Faculty of Computer Science, Institute of Business Administration, Karachi, Pakistan

    Quratulain Rajput

Authors
  1. Quratulain Rajput
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Editor information

Editors and Affiliations

  1. NLP Technologies Inc., 1255 University Street, H3B 3W9, Montreal, Quebec, Canada

    Atefeh Farzindar

  2. Dalhousie University, Faculty of Computer Science, 6050 University Ave, Halifax, B3H 1W5, Nova Scotia, Canada

    Vlado Kešelj

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Rajput, Q. (2010). Semantic Annotation Using Ontology and Bayesian Networks. In: Farzindar, A., Kešelj, V. (eds) Advances in Artificial Intelligence. Canadian AI 2010. Lecture Notes in Computer Science(), vol 6085. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13059-5_61

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  • DOI: https://doi.org/10.1007/978-3-642-13059-5_61

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13058-8

  • Online ISBN: 978-3-642-13059-5

  • eBook Packages: Computer ScienceComputer Science (R0)