Abstract
Automatic Terminology Extraction (ATE) is a technique for extracting phrases representing a dataset. This technique is required for translating specialistic books and documents. An existing method focused on the fact that terminologies tend to be composed of two or more single nouns. However, it does not deal with modification relations but only co-occurrence relations among single nouns. Moreover, we have to consider the fact that phrases defined as terminology tend to be explained in another sentence when we propose a novel approach. In this study, we propose a method for extracting terminologies from a dataset considering the modification relations obtained by dependency analysis. In particular, we propose how to extract features enabling us to distinguish whether or not the phrase is terminology from a dependency structure of a sentence.
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- 1.
Java Automatic Term Extraction: https://github.com/ziqizhang/jate.
- 2.
Research Purpose Use of NTCIR Test Collections or Data Archive/User Agreement: http://research.nii.ac.jp/ntcir/permission/perm-en.html#ntcir-1 (accessed on October 20th, 2020).
- 3.
Gensen Web: http://gensen.dl.itc.u-tokyo.ac.jp/gensenweb_eng.html. (accessed on November 27th, 2020).
- 4.
Japanese Dependency and Case Structure Analyzer KNP: http://nlp.ist.i.kyoto-u.ac.jp/EN/?KNP. (accessed on November 27th, 2020).
- 5.
Kurohashi, Kawahara, and Murawaki Laboratory (2018),
“Japanese Morphological Analysis System JUMAN++”, http://nlp.ist.i.kyoto-u.ac.jp/index.php?JUMAN++, (November 28th, 2020).
- 6.
Kurohashi, Kawahara, and Murawaki Lab (2018), “Japanese Syntactic, Case, and Linguistic Analysis System KNP”, http://nlp.ist.i.kyoto-u.ac.jp/?KNP, (November 28th, 2020).
- 7.
Hiroshi Nakagawa, Akira Maeda and Hiroyuki Kojima (2003), “Gensen Web” http://gensen.dl.itc.u-tokyo.ac.jp/, (November 28th, 2020).
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Acknowledgement
This study was partly supported by JSPS Research Grant (JP19H01138) and a grant for research promotion from the Graduate School of Culture and Information Studies, Doshisha University. The NTCIR1 test collection for terminology extraction research was provided by the National Institute of Informatics. We hereby express my gratitude.
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Kimura, Y., Kusu, K., Hatano, K., Baba, T. (2021). Automatic Terminology Extraction Using a Dependency-Graph in NLP. In: Abraham, A., Sasaki, H., Rios, R., Gandhi, N., Singh, U., Ma, K. (eds) Innovations in Bio-Inspired Computing and Applications. IBICA 2020. Advances in Intelligent Systems and Computing, vol 1372. Springer, Cham. https://doi.org/10.1007/978-3-030-73603-3_38
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