• Korean Journal of Cognitive Science
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• v.21 no.4
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• pp.459-480
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• 2010

A dialogue system includes various morphological analyses for recognizing a user's intention from the user's utterances. However, a user can represent various intentions via emotional states in addition to morphological expressions. Thus, a user's emotion recognition can analyze a user's intention in various manners. This paper presents a new method to automatically recognize a user's emotion for a dialogue system. For general emotions, we define nine categories using a psychological approach. For an optimal feature set, we organize a combination of sentential, a priori, and context features. Then, we employ a support vector machine (SVM) that has been widely used in various learning tasks to automatically classify a user's emotions. The experiment results show that our method has a 62.8% F-measure, 15% higher than the reference system.

• Proceedings of the Korean Information Science Society Conference
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• 2010.11a
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• pp.27-31
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• 2010

본 논문에서는 하이퍼그래프의 고유벡터를 척도로 하여 fMRI기반 Brain Network를 분석하여 중요한 허브노드를 찾는 방법론을 제시한다. 이 방법을 비디오게임을 수행하면서 촬영한 기능적 자기뇌영상(fMRI) 데이터인 PBAIC 2007 데이터셋에 대하여 그 유용성을 검증하였다. 이 데이터는 각 20분씩 세 세션을 촬영한 것이며 처음 두 세션에는 13가지의 감정 항목의 평가치가 각 스캔마다 주어진다. 한 피험자의 첫번째 세션 데이터로부터 13가지 감정 항목에 대하여 상관관계가 높은 각각의 복셀(voxel)들을 추출하였다. 이 13가지의 복셀들의 집합들을 각각 하이퍼에지로 보고 하이퍼그래프를 구성하였다. 하이퍼그래프로부 터 인접 행렬(adjacency matrix)를 구성한 후 고유치(eigenvalue)와 고유벡터(eigenvector)를 구하였다. 여기서 고유치가 가장 큰 고유벡터의 원소들은 각 복셀들의 중앙성(centrality), 즉 중요성을 나타내며 이로부터 감정과 관련된 중요한 허브 복셀들과 그들의 국소적 집합인 모듈을 찾았다. 모듈들은 감정 및 작업기억(working memory)과 관련된 뇌 영역들의 클러스터(cluster)로 추정된다.

• Journal of the Mineralogical Society of Korea
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• v.13 no.2
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• pp.73-83
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• 2000

다덕 광산 폐석내 섬아연석과 함망간탄산염 광물의 풍화현상과 그에 따른 중금속의 거동을 조사 하였다. 섬아연석은 풍화초기에 극미립 산화철의 망상구조 집합체로 교대되었으며, 후기에는 자연황이 용해중인 섬아연석과 산화철 집합체 사이에 침전되었다. 산화철 집합체에는 As가 다량 함유되어 있다. 능망간석와 함망간 방해석은 함아연산화망간의 망상구조 집합체로 교대되었으며, 함망간방해서과 함아연산화망간 사이에는 스미소나이트가 침전되었다. 선택적 용해외 X선회절분석을 이용하여 감정한 결과, 함아연산화망간은 헤테롤라이트/하이드로헤테롤라이트인 것으로 판명되었다. Zn의 일부는 규산과 결합하여 입간 공극에 월레마이트로 침전되었다. 풍화 초기에 형성되는 극미립 산화철 및 함아연산화망간의 치밀한 망상 집합체는 풍화용액의 순환을 차단하여, 모광물의 풍화 반응을 지체시키는 지화학적 장벽 역할을 하였다. 이에 따라 망상구조 내에 조성된 국지적 미환경하에서 풍화중간산물들이 침전되었다. 이상의 연구 결과로 다음과 같은 사항을 추론할 수 있다. 섬아연석의 Fe와 함망간탄산염의 Mn은 각각 산화철과 산화망간으로 침전되어 산성화에 기여하였다. 폐광석 더미내 As의 활동도는 저결정질 산화철에의 흡착에 의해 조절되며, Zn의 활동도는 미소환경조건에 따라 하이드로헤테롤라이트/헤테롤라이트, 스미소나이트, 월레마이트 등의 다양한 이차광물의 용해도에 의하여 조절된다.

• Journal of the Korea Society of Computer and Information
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• v.17 no.11
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• pp.133-140
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• 2012

In this paper, we propose a music recommendation method considering users' tags by collaborative tagging in a social music site. Since collaborative tagging allows a user to add keywords chosen by himself to web resources, it provides users' preference about the web resources concretely. In particular, emotional tags which represent human's emotion contain users' musical preference more directly than factual tags which represent facts such as musical genre and artists. Therefore, to classify the tags into the emotional tags and the factual tags and to assign weighted values to the emotional tags, a tag ontology called UniTag is developed. After preprocessing the tags, the weighted tags are used to create user profiles, and the music recommendation algorithm is executed based on the profiles. To evaluate the proposed method, a conventional playcount-based recommendation, an unweighted tag-based recommendation, and an weighted tag-based recommendation are executed. Our experimental results show that the weighted tag-based recommendation outperforms other two approaches in terms of precision.

• Journal of KIISE:Software and Applications
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• v.37 no.4
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• pp.317-322
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• 2010

This paper proposes how to improve performance of the Korean document sentiment-classification system using semantic properties of the sentiment words. A sentiment word means a word with sentiment, and sentiment features are defined by a set of the sentiment words which are important lexical resource for the sentiment classification. Sentiment feature represents different sentiment intensity in general field and in specific domain. In general field, we can estimate the sentiment intensity using a snippet from a search engine, while in specific domain, training data can be used for this estimation. When the sentiment intensity of the sentiment features are estimated, it is called semantic orientation and is used to estimate the sentiment intensity of the sentences in the text documents. After estimating sentiment intensity of the sentences, we apply that to the weights of sentiment features. In this paper, we evaluate our system in three different cases such as general, domain-specific, and general/domain-specific semantic orientation using support vector machine. Our experimental results show the improved performance in all cases, and, especially in general/domain-specific semantic orientation, our proposed method performs 3.1% better than a baseline system indexed by only content words.

• Journal of Software Assessment and Valuation
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• v.8 no.2
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• pp.13-27
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• 2012

This paper presents a tree-pattern based code-clone detector as CCR(Code Clone Ransacker) that finds all clusterd dulpicate pattern by comparing all pair of subtrees in the programs. The pattern included in its entirely in another pattern is ignored since only the largest duplicate patterns are interesed. Evaluation of CCR is high precision and recall. The previous tree-pattern based code-clone detectors are known to have good precision and recall because of comparing program structure. CCR is still high precision and the maximum 5 times higher recall than Asta and about 1.9 times than CloneDigger. The tool also include the majority of Bellon's reference corpus.

• Journal of Christian Education in Korea
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• v.71
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• pp.155-179
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• 2022

This study aims to apply Hannah Arendt's concept of 'collective responsibility' to the Christian education on environmental issues around the world, focusing on climate change. This study prepares the concept of 'collective responsibility' and the concept of 'collective guilt' and emphasizes the fact that the current climate change problem should be seen as a political task rather than a task of personal ethics. According to Arendt's theory, Christian education activities applying 'collective responsibility' for climate change can become action. This study has four suggestions for Christian learning to understand and recognize climate change. First, presenting and justifying the anxiety and anger toward climate change in the classroom. Second, transcending self-interest (egocentrism) through "Common Sense (enlarged mentality)" in Kantian terms. Third, building education communities through 'citizen participatory education,' running communication, and conversation. Fourth, encouraging experience and practice in every education community with "faith expressing itself through love (Gal 5:6)." Then, to be sure, this refers to not only love of neighbor in Christianity but also political friendship (philia politikē). The academic significance of this study is that it is the first interdisciplinary research paper in Korea which dealt with Arendt's political theory in relation to Christian education. Although it claims to be a theoretical work that applies Arendt's political theory from a systematic theological perspective to Christian education, the author is proud that it is accompanied by practical elements that can be actualized in the education field.

• Journal of the Korean Society for information Management
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• v.26 no.3
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• pp.451-462
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• 2009

The aim of this study is to apply latent semantic indexing(LSI) techniques for efficient automatic classification of opinionated documents. For the experiments, we collected 1,000 opinionated documents such as reviews and news, with 500 among them labelled as positive documents and the remaining 500 as negative. In this study, sets of content words and sentiment words were extracted using a POS tagger in order to identify the optimal feature set in opinion classification. Findings addressed that it was more effective to employ LSI techniques than using a term indexing method in sentiment classification. The best performance was achieved by a supervised LSI technique.

• 한국정보교육학회:학술대회논문집
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• 2006.01a
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• pp.179-184
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• 2006

초등학교 학급에서의 아동 상호간의 관계 파악은 아동 그룹이나 짝을 지어주고 교우관계를 분석하는데 매우 유용하다. 그러나 인간관계의 감정을 단순한 수치로 나타내기에는 아동 상호간의 복잡한 감정을 제대로 분석하기 힘들기 때문에, 본 논문에서는 퍼지 (Fuzzy) 이론을 기초로 하여 분석하고자 한다. 본 논문에서는 퍼지이론의 해밍거리(Hamming Distance)와 $\alpha$-수준집합을 적용하고 경향성을 계산할 수 있는 새로운 기법인 경향거리(Tendency Distance)를 제안하고 분석하는 기법을 연구하였다. 본 논문에서 제안하는 분석 방법의 특징은 첫째, 인간관계의 애매하고 모호한 점을 상대적 비교가 가능하게 함으로써 정확한 분석을 가능하게 하고, 둘째, 퍼지 이론의 적용을 통하여 해밍거리에 의한 유사도 분석에서 할 수 없었던 경향성의 분석을 가능하도록 하였으며, 셋째, 교육현장에서 발생할 수 있는 애매한 상황과 아동간의 교우 관계 등 수치적인 파악이 불가능한 부분을 분석이 가능한 데이터로 만들 수 있는 기법을 마련하였다는 데 의의를 둘 수 있다.

• Korean Journal of Cognitive Science
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• v.21 no.4
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• pp.669-696
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• 2010

Assuming that the whole meaning of a document is a composition of the meanings of each part, this paper proposes to study the automatic grading of movie reviews which contain sentimental expressions. This will be accomplished by calculating the values of semantic segments and performing data classification for each review. The ARSSA(The Automatic Rating System for Sentiment analysis using an Appraisal dictionary) system is an effort to model decision making processes in a manner similar to that of the human mind. This aims to resolve the discontinuity between the numerical ranking and textual rationalization present in the binary structure of the current review rating system: {rate: review}. This model can be realized by performing analysis on the abstract menas extracted from each review. The performance of this system was experimentally calculated by performing a 10-fold Cross-Validation test of 1000 reviews obtained from the Naver Movie site. The system achieved an 85% F1 Score when compared to predefined values using a predefined appraisal dictionary.