• Proceedings of the Korean Information Science Society Conference
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• 2006.06b
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• pp.4-6
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• 2006

본 논문은 자연언어처리에서 문장의 서술어와 그 서술어가 가지는 명사 논항들 사이의 문법관계를 의미 관계로 사상하는 즉 논항이 서술어에 대해 가지는 역할을 정하는 문제를 다루고 있다. 의미역 결정은 단어의 의미 중의성 해소와 함께 자연언어의 의미 분석의 핵심 문제 중 하나이며 반드시 해결해야 하는 매우 중요한 문제 중 하나이다. 본 연구에서는 언어학적으로 유용한 자원인 세종전자사전을 이용하여 용언격틀사전을 구축하고 격틀 선택 방법으로 의미역을 결정한 후. 결정된 의미역들에 대한 확률 정보를 확률 모델에 적용하여 반복적으로 학습하는 부트스트래핑(Bootstrapping) 알고리즘을 사용하였다. 실험 결과, 기본 모델에 대해 10% 정도의 성능 향상을 보였다.

• The KIPS Transactions:PartB
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• v.12B no.7 s.103
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• pp.829-840
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• 2005

Word Sense Disambiguation(WSD) is one of the most difficult problem in Korean information processing. We propose a WSD model with the capability to filter semantic information using the specific characteristics in dictionary dictions, and nth added information, useful to sense determination, such as statistical, distance and case information. we propose a model, which can resolve the issues resulting from the scarcity of semantic information data based on the word hierarchy system (thesaurus) developed by Ulsan University's UOU Word Intelligent Network, a dictionary-based toxicological database. Among the WSD models elaborated by this study, the one using statistical information, distance and case information along with the thesaurus (hereinafter referred to as 'SDJ-X model') performed the best. In an experiment conducted on the sense-tagged corpus consisting of 1,500,000 eojeols, provided by the Sejong project, the SDJ-X model recorded improvements over the maximum frequency word sense determination (maximum frequency determination, MFC, accuracy baseline) of $18.87\%$ ($21.73\%$ for nouns and inter-eojeot distance weights by $10.49\%$ ($8.84\%$ for nouns, $11.51\%$ for verbs). Finally, the accuracy level of the SDJ-X model was higher than that recorded by the model using only statistical information, distance and case information, without the thesaurus by a margin of $6.12\%$ ($5.29\%$ for nouns, $6.64\%$ for verbs).

• Korean Journal of Cognitive Science
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• v.26 no.4
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• pp.435-452
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• 2015

Recent researches on Entity Linking(EL) have attempted to disambiguate entities by using a knowledge base to handle the semantic relatedness and up-to-date information. However, EL for tweets using a knowledge base is still unsatisfactory, mainly because the tweet data are mostly composed of short and noisy contexts and real-time issues. The EL system the present work builds up links ambiguous entities to the corresponding entries in a given knowledge base via exploring the news articles and the user history. Using news articles, the system can overcome the problem of Wikipedia coverage (i.e., not handling real-time issues). In addition, given that users usually post tweets related to their particular interests, the current system referring to the user history robustly and effectively works with a small size of tweet data. In this paper, we propose an approach to building an EL system that links ambiguous entities to the corresponding entries in a given knowledge base through the news articles and the user history. We created a dataset of Korean tweets including ambiguous entities randomly selected from the extracted tweets over a seven-day period and evaluated the system using this dataset. We use accuracy index(number of correct answer given by system/number of data set) The experimental results show that our system achieves a accuracy of 67.7% and outperforms the EL methods that exclusively use a knowledge base.

• Journal of KIISE:Software and Applications
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• v.27 no.6
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• pp.668-677
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• 2000

Korean has the characteristics that case postpositions determine the syntactic roles of phrases and a postposition may have more than one meanings. In particular, the adverbial postpositions make translation from Korean to English difficult, because they can have various meanings. In this paper, we describe a method for resolving such semantic ambiguities of Korean adverbial postpositions using decision trees. The training examples for decision tree induction are extracted from a corpus consisting of 0.5 million words, and the semantic roles for adverbial postpositions are classified into 25 classes. The lack of training examples in decision tree induction is overcome by clustering words into classes using a greedy clustering algorithm. The cross validation results show that the presented method achieved 76.2% of precision on the average, which means 26.0% improvement over the method determining the semantic role of an adverbial postposition as the most frequently appearing role.

• Journal of the Korean Society for information Management
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• v.26 no.3
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• pp.261-278
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• 2009

Identifying optimal feature sets in Text Categorization(TC) is crucial in terms of improving the effectiveness. In this study, experiments on feature expansion were conducted using author provided keyword sets and article titles from typical scientific journal articles. The tool used for expanding feature sets is WordNet, a lexical database for English words. Given a data set and a lexical tool, this study presented that feature expansion with synonymous relationship was significantly effective on improving the results of TC. The experiment results pointed out that when expanding feature sets with synonyms using on classifier names, the effectiveness of TC was considerably improved regardless of word sense disambiguation.

• Proceedings of the Korea Contents Association Conference
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• 2006.05a
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• pp.231-234
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• 2006

Semantic web ontologies can be viewed as logic-based domain-oriented contents which allow distributed and heterogeneous information to be semantically integrated, automatically circulated, and enable implicit knowledge to be reasoned. This paper describes the 'Science and Technology Research Area' ontology which is being developed by the Korea Institute of Science and Technology Information (KISTI). This ontology was defined to assist actual researchers and project planners to grasp the researchers community from a variety of viewpoints. We describe classes and properties as ontology components and exemplify the representation of real instances in the ontology. In order to represent the identities of real world instances within the ontology, the above ontology employs both class-dependent URI assignment schemes and the identity resolution methods.

• Journal of Korean Classical Literature and Education
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• no.37
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• pp.111-149
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• 2018

This story is written by Shin Kwang-han who is a famous scholar and writer in Josun Dynasty. The most notable feature of this story is the love between a man and a dead woman. The protagonist has failed the test to be a national official for several years, because of the corruption and unfairness of the leaders of his society. He is very upset, but then changes his mind in order to become an officer. One day he meets a dead woman. He saves her life from death, and falls in love with her. Finally he marries her and attains a high position. Till now, all the aspects of this story have been extensively researched from a number of different perspectives. However the narrative structure of this story has not been discussed much. This story belongs to Jungi-novel, a kind of old story style which includes fantasy. The studies on this story have mostly been carried out to find the different features in comparison with other works of the same style. Further, we could not understand its own specific meaning structure. This study aims to find the narrative structure of this story. It was recognized by researchers that Shin's stories talk about his life and his perspective of the world. Further, I will try to show how he expresses his thoughts, emotion and life through this story. First, to obtain a satisfactory result through this study, I will find a way to resolve several problems that have become the center of the controversy. Afterward, the conflict and resolution the hero's relation to the world will be identified in every paragraph. Through these efforts, we will have a new point of the view about the narrative structure of this story and the intent expressed by the writer through its structure.

• Proceedings of the Korean Society of Postharvest Science and Technology of Agricultural Products Conference
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• 2003.04a
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• pp.98-98
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• 2003

무순에는 비타민 C가 많이 들어 있어 겨울철 비타민 공급원뿐만 아니라 디아스타제라는 효소가 들어 있어 소화를 촉진시키는 역할을 한다. 그 외에도 거담제 및 건위제 작용을 하고 음주로 인한 토혈해소, 천식에도 좋아 약용하기도 한다. 본 연구에서는 이용가치는 적지만 농가 소득증대에 기여 할 수 있으며 소화를 촉진시키는 무순, 또는 무싹기름이라고 일컬어지는 무순을 추출용매에 따라 생리활성 효과 분석하고 영양학적 가치가 가장 높은 시기의 무순을 선택함으로써 올바른 섭취의 기초자료를 마련하고 그 기능성을 확인하여 기능성 식품소재 및 기능성 화장품 소재로써의 활용을 검토하고자 하고자 한다. 무순을 4일, 8일, 12일에 따라 incubator에 배양하여 시기별로 채취하여 동결건조 한 후 70% Ethanol, 80% Methanol, 75% acetone, 열수로 환류 추출한 후 시료로 사용하였다. 각 용매 추출물에 대해 DPPH free radical 소거능 실험에서는 acetone 추출물에서 89.18%로 가장 높은 전자공여능을 나타냈으며 각각의 추출용매에서 성장 4일과 12일의 무순에서 높은 전자공여능을 보였다. 아질산염 소거능에서는 pH 1.2의 조건에서 가장 높은 아질산염 소거능을 보였고, 열수 추출물에서 89.70%로 가장 높은 소거능을 보였다. pH 4.2조건에서는 열수추출물의 소거능이 가장 좋았고, pH 6.0 조건에서는 가장 낮은 소거능을 보였으며, Ethanol 과 Methanol 추출물에서 23.55∼37.41%의 소거능을 보였다. SOD유사활성은 성장 8일에서 모두 낮은 활성을 보였으며, 성장 4일과 성장 12일의 무순에서는 큰 차이를 보이지 않았지만, Methanol 추출물중 성장 12일에서 27.41%의 SOD유사활성을 보였다.ic acid는 28.8∼51.7 mg%, 미강에서 321.4∼438.4 mg% 범위로 나타났다. 현미, 백미 및 미강에 함유된 총 폴리페놀의 함량을 표준 페놀화합물로 카테친을 사용하고 비색법에 의하여 측정하였을 때 오대 현미의 폴리페놀 함량은 78.4 mg%, 남평 현미 88.8 mg% 였다. 도정한 백미 중의 총 폴리페놀 함량은 30.3∼56.9 mg%, 미강이 541.5∼472.6 mg%의 범위였다. 이상과 같이 쌀에는 phenolic acid 및 총 폴리페놀이 상당량 함유되어 있으며 특히 배유보다는 강층에 많이 존재하므로 이들 성분의 효율적인 이용을 위한 쌀의 섭취방안이 필요한 것으로 나타났다. 유의적인 상관관계를 나타내고 있어 백편의 조직감은 Compression force 와 Work ratio로 대치할 수 있을 것이라고 사료된다. 수분함량은 기계적 검사보다 관능검사와 더욱 높은 상관관계를 나타냈다.내었다. 항균활성이 우수한 생약재를 농도별로 활성을 조사한 결과, 물 추출물과 10% Ethanol 추출물 모두 낮은 농도에서도 우수한 항균활성을 나타내었다.취와 함께 점질성 갈변물질이 생성되었다. 이와 같은 결과로 볼 때, BAAG의 처리는 BAAC의 경우보다 가격은 저렴하면서도 항균력은 우수한 천연 항균복합제재로써 농산물 식품원료에 적용하여 선도유지 기간을 연장할 수 있는 효과를 기대할 수 있었다. 과일 등의 포장제로서 이용할 가능성을 확인하였다.로 [-wh] 겹의문사는 복수 의미를 지닐 수 없 다. 그러면 단수 의미는 어떻게 생성되는가\ulcorner 본 논문에서는 표면적 형태에도 불구하고 [-wh]의미의 겹의문사는 병렬적 관계의 합성어가 아니라 내부구조를 지니지 않은 단순한 단어(minimal $X^{0}$ elem

• Journal of Korean Society of Transportation
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• v.22 no.7 s.78
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• pp.155-159
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• 2004

Recently, there are many trials about Artificial neural networks : ANNs structure and studying method of researches for forecasting traffic volume. ANNs have a powerful capabilities of recognizing pattern with a flexible non-linear model. However, ANNs have some overfitting problems in dealing with a lot of parameters because of its non-linear problems. This research deals with the application of a variety of model selection criterion for cancellation of the overfitting problems. Especially, this aims at analyzing which the selecting model cancels the overfitting problems and guarantees the transferability from time measure. Results in this study are as follow. First, the model which is selecting in sample does not guarantees the best capabilities of out-of-sample. So to speak, the best model in sample is no relationship with the capabilities of out-of-sample like many existing researches. Second, in stability of model selecting criterion, AIC3, AICC, BIC are available but AIC4 has a large variation comparing with the best model. In time-series analysis and forecasting, we need more quantitable data analysis and another time-series analysis because uncertainty of a model can have an effect on correlation between in-sample and out-of-sample.

• Korean Journal of Agricultural and Forest Meteorology
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• v.24 no.4
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• pp.275-284
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• 2022

Changes in air temperature, CO₂ concentration and precipitation due to climate change are expected to have a significant impact on soybean productivity. This study was conducted to evaluate the climate change impact on growth and development of determinate soybean cultivar in the southern parts of Korea. The high temperature during vegetative period, which does not accompany the increase of CO₂ concentration, increased the canopy photosynthetic rate in soybean, but after flowering, the high temperature above the optimal ranges interrupts the photosynthetic metabolism. In yield and yield components, high temperature reduced both the pod and seed number and single seed weight, resulting in a reduction of total seed yield. On the other hand, the increase in CO₂ concentration dramatically increased the canopy photosynthetic rate over the whole growth period. In addition, high CO₂ concentration increased the number of pods and seeds, which had a positive effect on total seed yield. Under concurrent elevation of air temperature and CO₂ concentration, canopy photosynthesis increased significantly, but enhanced canopy photosynthesis did not lead to an increase in soybean seed yield. The increase in biomass and branch by enhanced canopy photosynthesis seems to be attributed to an increase in the total number of pods and seeds per plant, which compensates for the negative effects of high temperature on pod development. However, Single seed weight tended to decrease rapidly by high temperature, regardless of CO₂ concentration level. Elevated CO₂ concentration did not compensate for the poor distribution of assimilations from source to sink caused by high temperature. These results show that the damage of future soybean yield and quality is closely related to high temperature stress during seed filling period.