• Language and Information
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• v.3 no.1
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• pp.39-63
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• 1999

Korean manner-of-motion verbs have different characteristics from locomotion verbs syntactically and semantically, and they are aptly encoded as having the primitive semantic element MOVE, not GO of Jackendoff(1990)'s Conceptual Semantics framework. This point is shown on the basis of their behavior, the inability to take the Goal 'NP-lo' phrases, the Purposive 'S-le' clauses, the 'NP-ey' phrases, and the atelic interpretation. It is further shown that the apparent locomotion verb behavior of some manner-of-motion verbs, 'exocentric' phenomenon in their meaning composition, is merely a transferred aspect of manner-of-motion verbs. Three kinds of strategies, transformational, quasi-transformational, and lexical ones, are examined to describe this phenomenon, and the lexical one is determined to be the most appropriate. The remaining part of this paper pursues the possibility of adopting Tenny's(1987, 1994) 'Aspectual Interface Hypothesis' in establishing an argument linking system with special attention to 'measuring-out', but concludes that the hypothesis can be accepted only in a restricted part of verbs, and with a modified notion of measuring-out like Jackendoff's(1996).

• Language and Information
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• v.18 no.2
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• pp.169-199
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• 2014

This study was performed to assume the Sematic role of the obligatory argument of the predicate in a Korean sentence, and to accomplish the task to attach the assumed thematic role to the real corpus. With this study, the maximum of the Sematic role was determined and the Criterion of the Sematic role was set. The maximum of the Sematic role was determined 22. This study arranged the Sematic role of case marker and attached the Sematic role to the predicate of the sentence within The standard Korean Dictionary. The program to attach the thematic role was developed(UTagger-SR). The Sematic role of case marker and Case frame dictionary was equipped in this program. By attaching the Sematic role, it was found that the most important the Sematic role in the korean sentence is the theme of the predicate and the next is the subject of the predicate.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.05a
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• pp.181-182
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• 2021

악성코드 분석방법의 발전에 따라 악성코드의 분석우회기법도 나날이 발전하여 대량의 악성코드분석이 다양한 이유로 수행되지 않고 있다. 대부분의 악성코드는 소스코드가 없는 바이너리로 동적 분석이 동작하지 않는 원인을 파악하기 어렵다. 동적 분석이 실행되지 않는 악성코드들은 입력 값에 따라 악성코드가 동작하거나, 특정 시간대를 일치하는 등 다양한 트리거가 존재한다. 본 논문에서는 트리거가 필요한 악성코드에 대해 바이너리 리프팅(lifting) 기술을 활용한 새로운 동적 분석방법을 제안한다. 바이너리 리프팅 기술은 소스코드가 없는 바이너리를 LLVM IR 로 변환시키는 기술로서 이를 활용해 입력 값 유무에 따른 악성코드를 판별하고자 한다. 전달인자를 사용하는 코드와 사용하지 않는 코드간 LLVM IR 을 비교분석하여 전달인자에 따른 악성코드 동작 여부를 판별해 대량의 악성코드 동적 분석시스템의 분석률을 높이는 방안을 제안하고자 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.626-628
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• 2021

사건 관계 추출 태스크는 구조화되지 않은 텍스트 데이터에서 사건의 구조화된 표현을 얻는 것이다. 하나의 문장에서도 많은 정보를 얻을 수 있는 중요한 태스크임에도 불구하고, 다양한 사전 학습 모델을 적용한 연구는 아직 활발하게 연구되지 않고 있다. 따라서 본 연구에서 사전 학습된 모델의 임베딩 기법 중 BERT, RoBERTa, SpanBERT에 각각 base, large 아키텍처를 적용하여 실험하였다. 사건을 식별하기 위한 trigger와 해당 trigger의 세부 argument를 식별하기 위한 분류기를 상위레이어로 각각 설계하였고, 다양한 배치 크기를 적용하여 실험하였다. 성능평가는 trigger/argument 각각 F1 score를 적용하였고, 결과는 RoBERTa large 모델에서 좋은 성능을 보인 것을 확인하였다.

• Journal of The Korean Association of Information Education
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• v.8 no.3
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• pp.417-432
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• 2004

The rapid development of ICT(Information and Communication Technology), beyond the argument of information society, has invoked discussion of knowledge-based society and enhanced the importance of the producing knowledge by using implementation of ICT. However, current computer education, without exactly defining the conception of ICT and direction of computer education, has great limitations in applying into education because it has mechanical characteristics and is not satisfying the demands of education that is supposed to bring up the creative human beings in current knowledge-based society. This study starts from the recognition of such problems. This paper explores the current computer education and argument. In addition, we researched necessity and direction of the computer education as subject matter.

• Journal of Information Technology Services
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• v.11 no.3
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• pp.49-65
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• 2012

This study aims to investigate the factors influencing followers' continuous usage intention of twitter based on Elaboration Likelihood Model. In particular, central route(information itself) and peripheral route(twitterian's trustworthiness) are tested to reveal which has a more influential role in effecting the continuous usage intention of power-twitter. Furthermore, this study tests the relationship of users' attitude and continuous usage intention. The results indicate that argument quality, accuracy(central route), source expertise and source trustworthiness (peripheral route) have an influence on attitude. However, trustworthy on central route is not significant. Argument quality, trustworthy, accuracy(central route) and source expertise(peripheral route) have an influence on perceived usefulness. But source trustworthiness on peripheral is not significant. Attitude has an influence on perceived usefulness, and attitude and perceived usefulness both have an influence on perceived usefulness. In conclusion, central route is more influential than peripheral route in forming a positive attitude towards arguments, which in turn leads to the perception of twitter's usefulness, and in the end brings the continuous usage intention of twitter.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.2
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• pp.299-308
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• 2019

As the utilization value of personal information becomes higher, discussions about providing personal information are being conducted actively. One of the most common methods of providing personal information is that a group obtains a personal information with a consent of individual. However, the above method has 2 problems. First, more information is exposed than the information required by organization for utilization of personal information. Second, trusted party should provide organization with an authentication of personal information whenever they require personal information. To solve these problems, we propose a personal information management system with blockchain using zk-SNARK(zero-knowledge Succinct Non-interactive ARgument of Knowledge) for privacy. Our proposal enables individuals to guarantee reliability of their information and protect their privacy concurrently using zk-SNARK when they provid organization with their personal information. In addition, it is possible to manage the personal information data while ensuring the integrity of the data using blockchain and it is possible to share the personal information more conveniently than existing systems.

• 한국어정보학회:학술대회논문집
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• 2016.10a
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• pp.111-116
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• 2016

의미역은 자연어 문장의 서술어와 관련된 논항의 역할을 설명하는 것으로, 주어진 서술어에 대한 논항인식(Argument Identification) 및 분류(Argument Labeling)의 과정을 거쳐 의미역 결정(Semantic Role Labeling)이 이루어진다. 이를 위해서는 격틀 사전을 이용한 방법이나 말뭉치를 이용한 지도 학습(Supervised Learning) 방법이 주를 이루고 있다. 이때, 격틀 사전 또는 의미역 주석 정보가 부착된 말뭉치를 구축하는 것은 필수적이지만, 이러한 노력을 최소화하기 위해 본 논문에서는 비모수적 베이지안 모델(Nonparametric Bayesian Model)을 기반으로 서술어에 가능한 의미역을 추론하는 비지도 학습(Unsupervised Learning)을 수행한다.

• Journal of the Korean Mathematical Society
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• v.49 no.4
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• pp.671-686
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• 2012

This paper mainly deals with the tilted Carath$\acute{e}$odory class by angle ${\lambda}$ ${\in}$ ($-{\pi}/2$, ${\pi}/2$), denoted by $P{\lambda}$) an element of which maps the unit disc into the tilted right half-plane {<${\omega}$ : Re $e^{i{\lambda}}{\omega}$ > 0}. Firstly we will characterize $P{\lambda}$ from different aspects, for example by subordination and convolution. Then various estimates of functionals over $P{\lambda}$ are deduced by considering these over the extreme points of $P{\lambda}$ or the knowledge of functional analysis. Finally some subsets of analytic functions related to $P{\lambda}$ including close-to-convex functions with argument ${\lambda}$, ${\lambda}$-spirallike functions and analytic functions whose derivative is in $P{\lambda}$ are also considered as applications.

• Annual Conference on Human and Language Technology
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• 2022.10a
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• pp.354-359
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• 2022

에세이 자동 평가는 주어진 에세이를 읽고 자동으로 평가하는 작업이다. 본 논문에서는 효과적인 에세이 자동 평가 모델을 위해 Argument Mining 작업을 사용하여 에세이의 논증 구조가 반영된 에세이 표현을 만들고, 에세이의 평가 항목별 표현을 학습하는 방법을 제안한다. 실험을 통해 제안하는 에세이 표현이 사전 학습 언어 모델로 얻은 표현보다 우수함을 입증했으며, 에세이 평가를 위해 평가 항목별로 다른 표현을 학습하는 것이 보다 효과적임을 보였다. 최종 제안 모델의 성능은 QWK 기준으로 0.543에서 0.627까지 향상되어 사람의 평가와 상당히 일치한다.