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박천식(Cheon-Sik Park),이시활(Si-Hwal Lee) 한국무역연구원 2021 무역연구 Vol.17 No.5
Purpose - Amid restrictions on international movement and decrease in overseas investment and trade due to COVID-19, this study analyzed the impact of asset size and age of overseas subsidiaries on exports and export costs of domestic parent companies. Design/Methodology/Approach - The samples used were 61,423 company-year date for the period covering 2011 to 2020 by the Korea Listed Companies Association TS2000 and KISVALUE. Findings - The results of empirical analysis were as follows. The asset size and age of overseas subsidiaries have a statistically significant positive impact on the total export volume of Korean parent companies and support the export complementary effect of overseas subsidiaries. In addition, the effects of characteristics of overseas subsidiaries on exports of goods and exports of product were examined separately, and results were not consistent. In the case of product exports, it can be interpreted that using an overseas subsidiary as a factor of production to reduce costs will result in the reimport of overseas produced products, thereby reducing the trade balance. Finally, subsidiary assets size and age have a significant positive effect on export costs. Research Implications - In conclusion, this suggests that if a company ownes an overseas subsidiary, it needs to enter the overseas market as early as possible and grow assets through proactive investment.
Multi-pass Sieve를 이용한 한국어 상호참조해결
박천음(Cheon-Eum Park),최경호(Kyoung-Ho Choi),이창기(Changki Lee) 한국정보과학회 2014 정보과학회논문지 Vol.41 No.11
상호참조해결은 문서 내에서 선행하는 명사구와 현재 등장한 명사구 간에 같은 개체를 의미하는 지를 결정하는 문제로 정보 추출, 문서분류 및 요약, 질의응답 등에 적용된다. 본 논문은 상호참조해결의 규칙기반 방법 중 가장 성능이 좋은 Stanford의 다 단계 시브(Multi-pass Sieve) 시스템을 한국어에 적용한다. 본 논문에서는 모든 명사구를 멘션(mention)으로 다루고 있으며, Stanford의 다 단계 시브 시스템과는 달리 멘션 추출을 위해 의존 구문 트리를 이용하고, 동적으로 한국어 약어 리스트를 구축한다. 또한 한국어 대명사를 참조하는데 있어 중심화 이론 중 중심의 전이적인 특성을 적용하여 가중치를 부여하는 방법을 제안한다. 실험 결과 F1 값은 MUC 59.0%, B3 59.5%, Ceafe 63.5%, CoNLL(평균) 60.7%의 성능을 보였다. Coreference resolution finds all expressions that refer to the same entity in a document. Coreference resolution is important for information extraction, document classification, document summary, and question answering system. In this paper, we adapt Stanford`s Multi-pass sieve system, the one of the best model of rule based coreference resolution to Korean. In this paper, all noun phrases are considered to mentions. Also, unlike Stanford`s Multi-pass sieve system, the dependency parse tree is used for mention extraction, a Korean acronym list is built ‘dynamically’. In addition, we propose a method that calculates weights by applying transitive properties of centers of the centering theory when refer Korean pronoun. The experiments show that our system obtains MUC 59.0%, B3 59.5%, Ceafe 63.5%, and CoNLL(Mean) 60.7%.
will과 would의 기본 의미 연구 -두 편의 영소설을 중심으로-
박천배 ( Cheon Bae Park ) 대한언어학회 2011 언어학 Vol.19 No.2
This thesis focuses on the typology and frequency analysis of various surface meanings of instances of "will" and "would" used in two English novels: Carroll (1865) Alice`s Adventures in Wonderland. and Hemingway (1929) A Farewell to Arms. The result of analysis shows that the meanings of "will" can be grouped chiefly into two types: volition and prediction. The count of occurrences shows that the proportion of ``volition`` is bigger than that of ``prediction`` by 43.9% and by 38.1% respectively, which leads us to conclude that the meaning of ``prediction`` can be considered as the basic lexical meaning of "will" and "would". However, considering the fact that the simple change of subject from the first person to the third person can replace the meaning of ``volition`` (e.g., I will help you) with that of ``prediction`` or simple future (e.g., He will help you), we should assume a bipolar axis of continuum consisting of ``prediction`` and "volition" for its core meanings in connection with the subjects of first person and third person. This axis of meanings, might as well be registered in the lexicon, just like the subcategorization for syntax.