Abstract
An ontology consists of a set and definition of concepts that presents the characteristics of a given domain and relationship between the elements. This paper proposes a semiautomatic method to construct a domain ontology using the results of text analysis and applies it to a document retrieval system. An experiment domain used to construct an ontology was selected by the pharmacy field in which the types of ontology appeared in a document were analyzed. By using these results, a processing method of the terminologies, which are combined with some specific nouns of suffices, and uses the semantic relation to construct an ontology. In order to present usefulness for retrieving a document using the hierarchical relations in an ontology, this study compares a typical keyword based retrieval method with an ontology based retrieval method, which uses related information in an ontology for a related feedback. As a result, the latter shows the improvement of precision and recall.
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References
Baeza-Yates, R., Robeiro-Neto, B.: Modern Information Retrieval. ACM Press, New York (1999)
Lee, G.-H., Lee, J.-H., Choi, M., Lim, G.-C.: Study on Named Entity Recognition in Korean Text. In: Proceedings of the 12th Conference on Hangul and Korean Information Processing, pp. 292–299 (2000)
Shin, H.-S., Kang, Y.-S., Choi, K.-S., Song, M.-S.: Computational Approach to Zero Pronoun Resolution in Korean Encyclopedia. In: Proceedings of the 13th Conference on Hangul and Korean Information Processing, pp. 239–243 (2001)
Oh, J., Lee, K., Choi, K.: Automatic Term Recognition using Domain Similarity and Statistical Methods. Journal of the Korea Information Science Society 29(4), 258–269 (2002)
Park, J.-O., Hwang, D.-S.: A Terminology extraction system. In: Proceedings of Korea Information Science Society Spring Conference(2001), vol. 27(1), pp. 381–383 (2000)
Klavans, J., Muresan, S.: DEFINDER:Rule-Based Methods for the Extraction of Medical Terminology and their Associated Definitions from On-line Text. In: Proceedings of AMIA Symposium, pp. 201–202 (2000)
Missikoff, M., Velardi, P., Fabriani, P.: Text Mining Techniques to Automatically Enrich a Domain Ontology. Applied Intelligence 18, 322–340 (2003)
Lim, S.-Y., Song, M.-H., Lee, S.-J.: Domain-specific Ontology Construction by Terminology Processing. Journal of the Korea Information Science Society(B), Journal of the Korea Information Science Society 31(3), 353–360 (2004)
Hwang, Y.-G., Yun, B.-H.: HMM-based Korean Named Entity Recognition. Journal of the Korea Information Procissing Society(B) 10(2), 229–236 (2003)
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© 2005 Springer-Verlag Berlin Heidelberg
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Lim, SY., Park, SB., Lee, SJ. (2005). Constructing an Ontology Based on Terminology Processing. In: Khosla, R., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2005. Lecture Notes in Computer Science(), vol 3681. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11552413_44
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DOI: https://doi.org/10.1007/11552413_44
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28894-7
Online ISBN: 978-3-540-31983-2
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