• Proceedings of the Korea Information Processing Society Conference
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• 2002.11a
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• pp.573-576
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• 2002

본 논문에서는 언어학의 관점에서 시제와 상의 특성을 알아 보고, Reichenbach 의 시제와 상을 살펴 보며, 상의 기술에 있어서 언어학자의 여러 주장과 문제점을 고찰하며, 한국어의 시제를 영어의 12 시제와 비교한다. 그리고 한국어의 여러 시제 의미를 분석하고, 시제의 구조를 개념그래프 이론에 의거하여 기술한다. 실험에서는 시제가 포함된 문장을 입력 받아 개념그래프로 변환하는 프로그램을 구현하고 그 결과를 기술한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2010.04a
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• pp.989-992
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• 2010

리팩토링은 시스템의 기능 변경 없이 코드 구조를 재조정하여 가독성을 높이고 유지보수성을 향상하기 위함이다. 기존의 어스팩트 리팩토링은 프로그램의 특정 부분을 어스팩트로 정의하여 리팩토링하거나 구현된 어스팩트 명세를 재구성하는 방식으로, 객체지향 프로그램에 적용하는데 어려움이 있다. 본 논문은 객체지향 리팩토링에 어스팩트 개념을 적용하기 위한 구체화된 접근방법을 제시하는 것이 목적이며 이를 위해 프로그램 의존성 그래프를 이용한다. 리팩토링의 주요 어스팩트인 중복 코드는 프로그램 의존 그래프에서 노드 사이의 순서관계를 비교하여, 리팩토링을 위한 어스팩트 후보로 변환하며 이를 근거로 재조합 함으로써 캡슐화된 객체 내부의 리팩토링 요소를 편리하게 처리할 수 있다.

• Annual Conference on Human and Language Technology
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• 2022.10a
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• pp.437-441
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• 2022

문맥 독립 주장 탐지는 논점에 대한 정보가 주어지지 않은 상황에서 문서 내부의 문장들 또는 단일 문장에 대한 주장을 탐지하는 작업이다. 본 논문에서는 GCN 계층을 통해 얻은 구조 정보와 사전 학습된 언어 모델을 통해 얻은 의미 정보를 활용하는 문맥 독립 주장 탐지 모델을 제안한다. 특히 문장의 전체 구조 정보를 나타내는 부모-자식 그래프와 문장의 특정 구조 정보를 나타내는 조부모-조손 그래프를 활용해 추가적인 구조 정보를 활용하여 주장 탐지 성능을 향상시켰다. 제안 모델은 IAM 데이터셋을 사용한 실험에서 기본 RoBERTa base 모델과 비교하여 최대 2.66%p의 성능 향상을 보였다.

• Annual Conference on Human and Language Technology
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• 2021.10a
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• pp.227-232
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• 2021

사실 검증(Fact verification) 문제는 문서 검색(Document retrieval), 증거 선택(Evidence selection), 증거 검증(Claim verification) 3가지 단계로 구성되어있다. 사실 검증 모델들의 주요 관심사인 증거 검증 단계에서 많은 모델이 제안되는 가운데 증거 선택 단계에 집중하여 강화 학습을 통해 해결한 모델이 제안되었다. 그래프 기반의 모델과 강화 학습 기반의 사실 검증 모델을 소개하고 각 모델을 한국어 사실 검증에 적용해본다. 또한, 두 모델을 같이 사용하여 각 모델의 장점을 가지는 부분을 병렬적으로 결합한 모델의 성능과 증거의 구성 단위에 따른 성능도 비교한다.

• Korean Journal of Food Science and Technology
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• v.37 no.3
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• pp.418-424
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• 2005

The physicochemical properties of raw noodle flours (n = 11) commercially produced from Australian Standard White (ASW) (Group 1, n = 8) and blonds (Group 2, n = 3) of ASW and Australian hard, western white or hard red winter were investigated. Protein and ash contents were lower in Group 1. The tristimulus color values, mean particle size, flour swelling volume (FSV) and rheological parameters of farinograph and extensigraph were not different between two flour groups. Peak viscosity measured with Rapid Visco Analyzer was higher in Group 1. The protein content was positively correlated with mean particle size, dough stability and dough extensibility, and negatively correlated with FSV and peak viscosity. The FSV wag positively correlated with the peak viscosity. The rheological parameters of dough did not show any correlations with FSV and peak viscosity.

• Journal of Korea Spatial Information System Society
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• v.9 no.2
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• pp.25-34
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• 2007

Existing approaches that select an order for the join of three or more data streams have always used the simple heuristics. For their disadvantage - only one factor is considered and that is join selectivity or arrival rate, these methods lead to poor performance and inefficiency In some applications. The graph-based sliding window multi -join algorithm with optimal join sequence is proposed in this paper. In this method, sliding window join graph is set up primarily, in which a vertex represents a join operator and an edge indicates the join relationship among sliding windows, also the vertex weight and the edge weight represent the cost of join and the reciprocity of join operators respectively. Then the optimal join order can be found in the graph by using improved MVP algorithm. The final result can be produced by executing the join plan with the nested loop join procedure, The advantages of our algorithm are proved by the performance comparison with existing join algorithms.

• Journal of the Korea Society of Computer and Information
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• v.16 no.8
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• pp.85-93
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• 2011

In this paper, we analyzed the function elements of the Integrated meter reading system based on PLC which is working in Mok-dong, Seoul and studied how to improve the vulnerability. Also we propose an efficient method for the estimation of abnormal life status through frequency domain processing of utility meter readings. We found out that even after removing the high-frequency components from the raw meter data, the shape of the graph still maintains the original graph characteristics. The graph of the inverse transformed data has simpler and smoother curve than the original graph pattern. The original graph is not good to be used in deciding whether the residence's life pattern is normal or not. We could find out that the graph which is processed frequency signal has simple and intuitive graph pattern.

• Applied Biological Chemistry
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• v.41 no.5
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• pp.367-371
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• 1998

The characteristics of four samples of noodle flours milled from Australian Standard White(ASW) wheat were compared with one sample of noodle flour prepared from a blend of hard red winter(HRW) and western white(WW) American wheats. The ASW flours had lower content of protein and ash. Farinograms revealed that the absorption of the ASW flours was slightly higher than that of the HRW-WW flour. The mixing time, however, showed no difference between ASW flours and HRW-WW flour. The stability and the mechanical tolerance index were different among ASW flours, which were lower than HRW-WW flour. The ratios of resistance to extention determined by extensigraph for ASW flours were higher except one flour than HRW-WW flour. The flours showed characteristic mean particle sizes, which may reflect the differences in hardness of wheat used in the flour production. Farinograph indices showed no correlations with protein content and extensigraph indices. The amylograph peak viscosity was inversely correlated with the protein content (p<0.05).

• Journal of Korean Society of Archives and Records Management
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• v.20 no.4
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• pp.1-17
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• 2020

Along with the development of information technology, the digitalization of archives has also been accelerating. However, digital archives have limitations in effectively searching, interlinking, and understanding records. In response to these issues, this study proposes a knowledge graph that represents comprehensive relationships among heterogeneous entities in digital archives. In this case, the knowledge graph organizes resources in the archives on the Korean financial crisis of 1997 by transforming them into named entities that can be discovered by machines. In particular, the study investigates and creates an overview of the characteristics of the archives on the Korean financial crisis as a digital archive. All resources on the archives are described as entities that have relationships with other entities using semantic vocabularies, such as Records in Contexts-Ontology (RiC-O). Moreover, the knowledge graph of the Korean Financial Crisis of 1997 is represented by resource description framework (RDF) vocabularies, a machine-readable format. Compared to conventional digital archives, the knowledge graph enables users to retrieve a specific entity with its semantic information and discover its relationships with other entities. As a result, the knowledge graph can be used for semantic search and various intelligent services.

• Journal of Digital Convergence
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• v.11 no.11
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• pp.409-414
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• 2013

Naive Bayesian classifiers are a powerful and well-known type of classifiers that can be easily induced from a dataset of sample cases. However, the strong conditional independence assumptions can sometimes lead to weak classification performance. Normally, naive Bayesian classifiers use Gaussian distributions to handle continuous attributes and to represent the likelihood of the features conditioned on the classes. The probability density of attributes, however, is not always well fitted by a Gaussian distribution. Another eminent type of classifier is the neuro-fuzzy classifier, which can learn fuzzy rules and fuzzy sets using supervised learning. Since there are specific structural similarities between a neuro-fuzzy classifier and a naive Bayesian classifier, the purpose of this study is to apply learning distribution graphs constructed by a neuro-fuzzy network to naive Bayesian classifiers. We compare the Gaussian distribution graphs with the fuzzy distribution graphs for the naive Bayesian classifier. We applied these two types of distribution graphs to classify leukemia and colon DNA microarray data sets. The results demonstrate that a naive Bayesian classifier with fuzzy distribution graphs is more reliable than that with Gaussian distribution graphs.