Abstract
Ontology means terms used in a specific domain, the definition of relationships among the terms, and the expression of the relationships in a hierarchical structure. This study suggests a method of constructing domain ontology using terminology processing and applies the method to document retrieval. In order to construct ontology, it proposes an algorithm that classifies the patterns of nouns and suffices which compose terminology, in domain texts, extracts terminology, and build a hierarchical structure. The experiment used documents related to pharmacy, and the algorithm showed accuracy of 92.57% for singleton terms and 66.64% for multi-word terms on the average. Constructed ontology, which forms natural groups of senses centering on specific nouns or suffices composing the terminology with semantic information, can be utilized in approaching the knowledge of special areas such as document retrieval. According to the result of document retrieval based on the constructed ontology, the system improved accuracy by 14.28% compared to keyword-based document retrieval.
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References
Baeza-Yates, R., Robeiro-Neto, B.: Modern Information Retrieval. ACM Press, New York (1999)
Bettina, B., Andreas, H., Gerd, S.: Towards Semantic Web Mining. In: International Semantic Web Conference (2002)
Guarino, N.: Formal Ontology and Information Systems. In: Proceeding of the 1st International Conference, lOS Press, Trento (1998)
Kang, S.J., Lee, J.H.: Semi-Automatic Practical Ontology Construction by Using a Thesaurus, Computational Dictionaries, and Large Corpora. In: ACL 2001 Workshop on Human Language Technology and Knowledge Management, Toulouse, France (2001)
Lim, S.Y., Koo, S.O., Song, M.H., Lee, S.: Hub_word based on Ontology Construction for Document Retrieval. In: IC-AI 2003, Las Vegas, USA (2003)
Maedche, A.: Ontology Learning for the Semantic Web. Kluwer Academic Publishers, Boston (2002)
Smith, M.K., Welty, C., McGuinness, D.L.: OWL Web Ontology Language Guide. In: World Wide Web Consortium (2003), http://www.w3.org/TR/owl-guide
Michele, M., Paola, V., Paolo, F.: Text Mining Techniques to Automatically Enrich a Domain Ontology. Applied Intelligence 18, 322–340 (2003)
Oh, J.-H., Lee, K.-S., Choi, K.-s.: Automatic Term Recognition using Domain Similarity and statistical Methods. Korean Journal of Cognitive Science 29(4), 258–269 (2002)
Lee, H.-M., Park, H.-R.: A Reverse Segmentation Algorithm of Compound Nouns. Korea Information Processing Society Journal(B) 8-B(4), 357–364 (2003)
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© 2004 Springer-Verlag Berlin Heidelberg
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Lim, SY., Song, MH., Lee, SJ. (2004). The Construction of Domain Ontology and Its Application to Document Retrieval. In: Yakhno, T. (eds) Advances in Information Systems. ADVIS 2004. Lecture Notes in Computer Science, vol 3261. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30198-1_13
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DOI: https://doi.org/10.1007/978-3-540-30198-1_13
Publisher Name: Springer, Berlin, Heidelberg
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