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Ontology acquisition and semantic retrieval from semantic annotated chinese poetry

Published:07 June 2004Publication History

ABSTRACT

This research aims to utilize semantic web[1]. technology to the semantic annotation of classical Chinese poetry. We investigate the feasibilities and advantages of semantic retrieval and automated ontology acquisition from semantically annotated poems based on a Chinese thesaurus. We have induced a set of semantic composition rules for pair-wise character (word) patterns that can be used to parse the poem sentences and recursively generate RDF[2]. triple relations among the pair of characters (words). We have also defined a scoring scheme to assess semantic similarity for semantic retrieval. We showed that the semantic retrieval method significantly outperformed the keyword-based retrieval method.

References

  1. James Hendler, Tim Berners-Lee, and Eric Miller, "Integrating Applications on the Semantic Web," Journal of the Institute of Electrical Engineers of Japan, Vol 122(10), October, 2002, pp. 676--680, <http://www.w3.org/2001/sw/>.Google ScholarGoogle ScholarCross RefCross Ref
  2. "Resource Description Framework (RDF) Model and Syntax Specification W3C Recommendation 22, February, 1999", <http://www.w3.org/RDF/>.Google ScholarGoogle Scholar
  3. "Classical Chinese Poetry", http://en.wikipedia.org/wiki/Chinese_Poetry.Google ScholarGoogle Scholar
  4. Mei et al. "TongyiciCilin Thesaurus", Commercial Press, Shanghai,1996. Von-Wun Soo, Chen-Yu Lee, Chung-Cheng Lin, Shu Lei Chen and Ching-chih Chen, "Automated Semantic Annotation and Retrieval Based on Sharable Ontology and Case-based Learning Techniques", In the Proceedings of JCDL 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. Ontology acquisition and semantic retrieval from semantic annotated chinese poetry

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    • Published in

      cover image ACM Conferences
      JCDL '04: Proceedings of the 4th ACM/IEEE-CS joint conference on Digital libraries
      June 2004
      440 pages
      ISBN:1581138326
      DOI:10.1145/996350

      Copyright © 2004 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 7 June 2004

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      Acceptance Rates

      JCDL '04 Paper Acceptance Rate61of249submissions,24%Overall Acceptance Rate415of1,482submissions,28%

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