There have been many studies of automatic term recognition (ATR) and they have achieved good results. However, they focus on a mono-lingual term extraction method. Therefore, it is difficult to extract terms from documents in foreign languages. This article describes an automatic term extraction method from documents in foreign languages using a machine translation system. In our method, we translate documents in foreign languages into documents in Korean and extract terms in the translated Korean documents. Finally the terms recognized from the Korean documents are translated into terms in the foreign language. By using our method, one can extract terms for languages, which one does not know.
2018. Developing a frequent technical words list for finance: A hybrid approach. English for Specific Purposes 51 ► pp. 45 ff.
Tangpijaikul, Montri
2014. Preparing Business Vocabulary for the ESP Classroom. RELC Journal 45:1 ► pp. 51 ff.
Wilks, Yorick A.
2005. Unhappy Bedfellows: The Relationship of AI and IR. In Charting a New Course: Natural Language Processing and Information Retrieval [The Kluwer International Series on Information Retrieval, 16], ► pp. 255 ff.
Chung, Teresa Mihwa & Paul Nation
2004. Identifying technical vocabulary. System 32:2 ► pp. 251 ff.
OH, JONG-HOON & KEY-SUN CHOI
2003. A Statistical Model for Automatic Extraction of Korean Transliterated Foreign Words. International Journal of Computer Processing of Languages 16:01 ► pp. 41 ff.
This list is based on CrossRef data as of 10 july 2024. Please note that it may not be complete. Sources presented here have been supplied by the respective publishers.
Any errors therein should be reported to them.