• Korean Journal of Cognitive Science
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• v.21 no.1
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• pp.157-175
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• 2010

Understanding dialogue participant's emotion is important as well as decoding the explicit message in human communication. It is well known that non-verbal elements are more suitable for conveying speaker's emotions than verbal elements. Written texts, however, contain a variety of linguistic units that express emotions. This study aims at analyzing components for constructing an emotion ontology, that provides us with numerous applications in Human Language Technology. A majority of the previous work in text-based emotion processing focused on the classification of emotions, the construction of a dictionary describing emotion, and the retrieval of those lexica in texts through keyword spotting and/or syntactic parsing techniques. The retrieved or computed emotions based on that process did not show good results in terms of accuracy. Thus, more sophisticate components analysis is proposed and the linguistic factors are introduced in this study. (1) 5 linguistic types of emotion expressions are differentiated in terms of target (verbal/non-verbal) and the method (expressive/descriptive/iconic). The correlations among them as well as their correlation with the non-verbal expressive type are also determined. This characteristic is expected to guarantees more adaptability to our ontology in multi-modal environments. (2) As emotion-related components, this study proposes 24 emotion types, the 5-scale intensity (-2~+2), and the 3-scale polarity (positive/negative/neutral) which can describe a variety of emotions in more detail and in standardized way. (3) We introduce verbal expression-related components, such as 'experiencer', 'description target', 'description method' and 'linguistic features', which can classify and tag appropriately verbal expressions of emotions. (4) Adopting the linguistic tag sets proposed by ISO and TEI and providing the mapping table between our classification of emotions and Plutchik's, our ontology can be easily employed for multilingual processing.

• Journal of The Korean Association For Science Education
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• v.39 no.6
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• pp.767-775
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• 2019

This study was conducted to analyze explicit and implicit teaching cases of scientific terms in accordance with the 2015 revised curriculum, pointing out the problems of current textbooks in terms of scientific terms education and proposing method to improve them. Scientific terms used in eight science textbooks of 2015 revised curriculum, third and sixth graders of elementary school, first graders of middle school and first graders of high school were extracted, and cases used explicitly and implicitly were collected and analyzed. Brief summary of the results of the study is as follows. First, scientific terms were used in elementary, middle, and high school science textbooks at a rate of about 15 to 30 percent of the total vocabulary contained in the textbooks, which is on average more than five times larger than those in foreign countries based on the number of scientific terms included on each page. Second, among the scientific terms used in science textbooks, the percentage of scientific terms in which semantic education is achieved through explicit means was 9.7 to 18.8 percent, which naturally means that the remaining 80 percent or more of the scientific terms are presented in the form of implicit education. Third, even though the ratio of explicit term education should be higher in the lower grades, the ratio of explicit term education in elementary schools was lower than 10% in the sixth grade.

• Korean Journal of Clinical Pharmacy
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• v.17 no.1
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• pp.6-12
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• 2007

The clinical investigations above suggest that topiramate may be an effective agent in the treatment of BED or BN by reducing binging/purging episodes, improving the HRQOL, and decreasing weight. The case report and case series also support these findings. However, there are several limitations in the above studies and cases. All these had relatively small sample size, and two of them were only 10-week-period studies. Optimal duration of treatment with topiramate in patients with BED or BN is unknown. As most clinicians treat the patient with BED or BN for 6 to 12 months and then reassess, at least 6 months period is needed to show its efficacy. One of studies included only women in the patient group. In the case series, all patients had severe comorbid mood disorders such as major depression and bipolar disorder besides BN. Therefore, notwithstanding its clinical usefulness, additional researches are needed to define the role and the benefits of topiramate in the treatment of BED or BN more thoroughly.

• Journal of the Korea Convergence Society
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• v.9 no.1
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• pp.419-431
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• 2018

In this paper, we propose a novel method for monitoring mood trend of Twitter users by analyzing their daily tweets for a long period. Then, to more accurately understand their tweets, we analyze all types of content in tweets, i.e., texts and emoticons, and images, thus develop a multimodal sentiment analysis method. In the proposed method, two single-modal analyses first are performed to extract the users' moods hidden in texts and images: a lexicon-based and learning-based text classifier and a learning-based image classifier. Thereafter, the extracted moods from the respective analyses are combined into a tweet mood and aggregated a daily mood. As a result, the proposed method generates a user daily mood flow graph, which allows us for monitoring the mood trend of users more intuitively. For evaluation, we perform two sets of experiment. First, we collect the data sets of 40,447 data. We evaluate our method via comparing the state-of-the-art techniques. In our experiments, we demonstrate that the proposed multimodal analysis method outperforms other baselines and our own methods using text-based tweets or images only. Furthermore, to evaluate the potential of the proposed method in monitoring users' mood trend, we tested the proposed method with 40 depressive users and 40 normal users. It proves that the proposed method can be effectively used in finding depressed users.

• Proceedings of the Korean Society for Cognitive Science Conference
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• 2000.05a
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• pp.303-308
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• 2000

용언은 그 어간이 여러 문법소와 결합하면서 자동적 음운 변동을 제외한 형태 변동이 있는가, 없는가에 의해 규칙 용언/불규칙 용언으로 구분할 수 있다. 이러한 불규칙 용언은 심성 어휘집에 어떤 형태로 저장되어 있으며, 규칙 용언과는 어떠한 관계가 있는지, 나아가 실어증 환자의 경우에는 정상인에 비해 어떤 행동장애를 보이며, 장애가 있다면 어느 경로의 손상으로 인한 장애인지를 알아보는 것이 본 연구의 목적이다. 이를 위해 이해성 실어증 환자 한 명과 음어적 실행증 현상을 동반한 경미한 정도의 실어증 환자를 피험자로 하였다. 실험 과제는 단어 채워 넣기 과제(word completion task)를 사용하였다. 즉 주어진 기본형 용언을 검사 문장의 문맥에 맞게 활용하여 채워 넣는 것이다. 실험 결과에 의하면 환자들은 규칙용언의 활용(예. 먹다/먹는)과 불규칙 용언 중 형태를 유지한 채로 활용하는 경우(예. 줍다/줍고)에는 거의 오류가 없었으나, 불규칙 용언이 형태 변화를 겪어야 할 경우(예. 줍다/주워)에는 대부분 오류를 보였다. 또 이때는 기본형(basic form)을 그대로 유지하는 오류 방향성을 관찰할 수 있었다. 이는 그간 문법으로 구분되어 오던 규칙 용언/불규칙 용언의 정보 처리보다는 형태 유지/형태 변화 정보 처리의 영향이 크다는 것을 알 수 있다. 특히 이해성 실어증 환자는 전체적인 오류율이 매우 높았는데, 규칙 용언의 경우에도 오류를 보였다. 이때, 용언의 어간에 해당하는 부분에는 오류가 없고, 뒤에 따르는 내용과의 관계를 파악해야 하는 문법 기능소, 즉 연결 어미에서 오류를 보여 정보의 유지, 통합에 문제가 있다는 기존의 연구와도 일치하는 결과를 나타냈다.환자는 시제 선어말 어미를 선택하는데도 어려움을 보임이 확인되었다. 실험 3 역시 실험 1과 실험2에서와 동일하게 처리의 어려움을 보였다. 이러한 실험 결과들은 국어의 존칭과 시제 선어말 어미가 통사부에서 구(XP)와 결합하여 새로운 구를 형성하는 통사적 접사로 해석할 수 있으며 Grodzinsky의 가설을 지지하는 결과를 보여 줌으로서 국어에서도 AgrP, TP, CP 사이의 통사적 위계가 있음을 뒷받침하는 증거가 된다.전처리한 Group 3에서는 IL-2와 IL-4의 수준이 유의성있게 억제되어 발현되었다 (p < 0.05). 이러한 결과를 통하여 T. denticola에서 추출된 면역억제 단백질이 Th1과 Th2의 cytokine 분비 기능을 억제하는 것으로 확인 되었으며 이 기전이 감염 근관에서 발견되는 T. denticola의 치수 및 치근단 질환에 대한 병인기전과 관련이 있는 것으로 사료된다.을 보였다. 본 실험 결과, $Depulpin^{\circledR}은{\;}Tempcanal^{\circledR}와{\;}Vitapex^{\circledR}$에 비해 높은 세포 독성을 보여주공 있으나, 좀 더 많은 임상적 검증이 필요할 것으로 사료된다.중요한 역할을 하는 것으로 추론할 수 있다.근관벽을 처리하는 것이 필요하다고 사료된다.크기에 의존하며, 또한 이러한 영향은 $(Ti_{1-x}AI_{x})N$ 피막에 존재하는 AI의 함량이 높고, 초기에 증착된 막의 업자 크기가 작을 수록 클 것으로 여겨진다. 그리고 환경의 의미의 차이에 따라 경관의 미학적 평가가 달라진 것으로 나타났다.corner$적 의도에 의한 경관구성의 일면을 확인

• Archives of design research
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• v.17 no.4
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• pp.141-148
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• 2004

The purpose of this study is to define the emotion that expressed in step animation and to quantify the intuitional expression of emotion that related step for using extract, measure, analysis the stimulate element about step. The survey of relation with 27 word of emotional expressions and 36 moving pictures of step sample is used for method of this test. The emotional mental structure is transferred to 2 dimensional planes as applying the results of analysis of integrated data using Quantification Method 3, which the integrated data is composed two axial - confidential axial and stabling axial. Analysis of distribution of 2 dimensional diagram shows that the second of the plane and the third of the plane have much data. However, the first of the plane and the forth of the plane have a little data. Through this kind of analysis of graph, it is difficult to express a different emotion between unstable the timidity mind and stable feel the timidity mind using only step analysis. Six difference types about physical elements affecting to emotion are selected and analyzed such as the paces of step, the rate of step, the movement angle of pelvis, the swing range of arm, angle of backbone and the lean angle of body. The result is that the rate of stop and the lean angle of body are the major element that effects to emotional stimulate of stop. This thesis argues about methods transforming subjective expression to objective and quantitative expression with the state of delicate emotion of character apply to step animation naturally. Those data to apply to multi-contents in future are the main target in this study.

• Archives of design research
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• v.19 no.2 s.64
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• pp.343-354
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• 2006

Human emotion is the issue which is subjective, difficult to define and even more difficult to measure because it's personal. In general, the methods for measuring human emotion is divided in two, one is the psychological way based on user's subjective evaluation and another is the physiological way based on physiological signs. However, these methods have some limitations. Therefore, in this study we suggested the methods for measuring users emotion in the natural and accessible environment for the design field. In order to observe user's emotional changes while they interact with a product, we have extracted some emotional words and representative emotions, and made a set of subjective evaluation scales. With these scales, emotion logging program 'VideoTAME' was developed as an effective measurement tool for complementing the current psychological methods. In the testing module of 'VdeoTAME,' participants evaluate their emotional changes through playing and watching the video dips of their performing tasks in the experiment room. In the analyzing module, the researchers replay the results created by participants during the experiment and analyze the results using Microsoft Exel. It is hoped that this study will be of great help for designers for effective measurement of user's emotions naturally expressed while using a product.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.1
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• pp.35-42
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• 2013

Developing English-Korean machine translation system requires the construction of information about the languages, and the amount of information in English-Korean transfer dictionary is especially critical to the translation quality. Newly created words are out-of-vocabulary words and they appear as they are in the translated sentence, which decreases the translation quality. Also, compound nouns make lexical and syntactic analysis complex and it is difficult to accurately translate compound nouns due to the lack of information in the transfer dictionary. In order to improve the translation quality of English-Korean machine translation, we must continuously expand the information of the English-Korean transfer dictionary by collecting the out-of-vocabulary words and the compound nouns frequently used. This paper proposes a method for expanding of the transfer dictionary, which consists of constructing corpus from internet newspapers, extracting the words which are not in the existing dictionary and the frequently used compound nouns, attaching meaning to the extracted words, and integrating with the transfer dictionary. We also develop the tool supporting the expansion of the transfer dictionary. The expansion of the dictionary information is critical to improving the machine translation system but requires much human efforts. The developed tool can be useful for continuously expanding the transfer dictionary, and so it is expected to contribute to enhancing the translation quality.

• Smart Media Journal
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• v.11 no.5
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• pp.17-25
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• 2022

Korean part-of-speech taggers decompose a compound morpheme into unit morphemes and attach part-of-speech tags. So, here is a disadvantage that part-of-speech for morphemes are over-classified in detail and complex word types are generated depending on the purpose of the taggers. When using the part-of-speech tagger for keyword extraction in deep learning based language processing, it is not required to decompose compound particles and verb-endings. In this study, the part-of-speech tagging problem is simplified by using a Head-Tail tokenization technique that divides only two types of tokens, a lexical morpheme part and a grammatical morpheme part that the problem of excessively decomposed morpheme was solved. Part-of-speech tagging was attempted with a statistical technique and a deep learning model on the Head-Tail tokenized corpus, and the accuracy of each model was evaluated. Part-of-speech tagging was implemented by TnT tagger, a statistical-based part-of-speech tagger, and Bi-LSTM tagger, a deep learning-based part-of-speech tagger. TnT tagger and Bi-LSTM tagger were trained on the Head-Tail tokenized corpus to measure the part-of-speech tagging accuracy. As a result, it showed that the Bi-LSTM tagger performs part-of-speech tagging with a high accuracy of 99.52% compared to 97.00% for the TnT tagger.

• Journal of Korea Entertainment Industry Association
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• v.13 no.4
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• pp.93-106
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• 2019

Persona is an actor's external ego constructed by playing various roles, and his/her another self-portrait in the eyes of the audience. This study was conducted to analyze persona identity containing core persona(CP) and to gain implications for the growth strategy of the actress Son Ye-jin called "melo queen" by verifying consistency between the CP and audience responses to her starring works of the past. According to the related theories and models, the persona was firstly set as image, visuality, personality and consistency, and it was used to extract and sort descriptive texts about Son related news articles in the last 5 years of the six major Korean newspapers using the content analysis method. After that, we analyzed the number of viewers of her movies and the audience share of her dramas by genre. As a result, Son's persona components were found to have a proportion for 54.2% images (34.0% for melo and romance images, 20.2% for non-melo and romance images), 25.6% for visibility, 13.8% for consistency, and 6.4% for personality. Her CP was derived from a melo and romance image. Comparing this with the audience reaction, the melo romance genre dominated and showed consistency in the drama, but in the case of the film, the non-melo romance was dominant and did not match each other. The results were attributed to a wide gap between dramas and movies in terms of key viewers, box office factors, degree of genre hybridity and experimentality. Therefore, Son should actively use her CP in the drama and challenge the various roles in order to expand her persona spectrum in the film.