• The Journal of the Korea Contents Association
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• v.7 no.2
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• pp.246-254
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• 2007

As for comics and animation, the specific gravity came to become still larger in all the art fields together with the importance in various image media now which is useful and goes the time of the 21st century new media. Especially the demand of users to the vision culture which develops day by day, Sensitivity Engineering Department is trying to realize the necessity for a sensitivity design acutely together. The influence of the comics which have toxicity most also in Japanese culture in a geographical position like South Korea on it, and animation is the actual condition in the reason which has reached from youth universally to the layer for years, to be inquired systematic to a Korean comics language. This research was conducted as we thought sufficient study on various situations are required, and among them for the research of expressions of cartoons's characters, we've divided the expressions of characters that comes out in Japanese cartoons into categories of 'happiness, anger, sadness, pleasure' and 'fear, astonishment and dislike' and based on these categories, we've drawn out the minimum elements to express emotions in cartoon and prepared image-map by relating them with languages that express emotions of people and based on this, we've made a calculating tools on how our readers would recognize the expression languages. Samples of Japanese cartoons of which we've chosen for the purpose of drawing out the elements of expressions were limited to only published cartoons and we've made a foot steps for expression analysis of animation characters in the future.

• Annual Conference on Human and Language Technology
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• 2021.10a
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• pp.320-325
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• 2021

BERT는 사전 학습 단계에서 다음 문장 예측 문제와 마스킹된 단어에 대한 예측 문제를 학습하여 여러 자연어 다운스트림 태스크에서 높은 성능을 보였다. 본 연구에서는 BERT의 사전 학습 문제 중 다음 문장 예측 문제에 대해 주목했다. 다음 문장 예측 문제는 자연어 추론 문제와 질의 응답 문제와 같이 임의의 두 문장 사이의 관계를 모델링하는 문제들에 성능 향상을 위해 사용되었다. 하지만 BERT의 다음 문장 예측 문제는 두 문장을 특수 토큰으로 분리하여 단일 문자열 형태로 모델에 입력으로 주어지는 cross-encoding 방식만을 학습하기 때문에 문장을 각각 인코딩하는 bi-encoding 방식의 다운스트림 태스크를 고려하지 않은 점에서 아쉬움이 있다. 본 논문에서는 기존 BERT의 다음 문장 예측 문제를 확장하여 bi-encoding 방식의 다음 문장 예측 문제를 추가적으로 사전 학습하여 단일 문장 분류 문제와 문장 임베딩을 활용하는 문제에서 성능을 향상 시키는 Bi-Cross 사전 학습 기법을 소개한다. Bi-Cross 학습 기법은 영화 리뷰 감성 분류 데이터 셋인 NSMC 데이터 셋에 대해 학습 데이터의 0.1%만 사용하는 학습 환경에서 Bi-Cross 사전 학습 기법 적용 전 모델 대비 5점 가량의 성능 향상이 있었다. 또한 KorSTS의 bi-encoding 방식의 문장 임베딩 성능 평가에서 Bi-Cross 사전 학습 기법 적용 전 모델 대비 1.5점의 성능 향상을 보였다.

• Journal of Korea Entertainment Industry Association
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• v.14 no.4
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• pp.67-75
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• 2020

Metonymy can be said to be the only language's meaning shifting technique that exists in the domain of a single human thought in order to obtain a transparent cognitive effect. The purpose of this study was to analyze the 'descriptive metonymy' of the advertising content language constructed by the cognitive principle and to find a way to use it in media language education for social and cultural interests and reflection of college students. The metonymy used in advertising media contrasts with the difficulty of the metaphorical interpretation of "opaque and distant" reasoning. Storyboards, mostly focused on human emotions and behaviors, used metonymy's 'transparent and easy meaning shifting technique'. I have found that I can expect the efficiency of media language education that contains the interest and sociocultural interest, self-reflection, and future imagination of college students. Now, there is less need to perform cognitive reasoning for advertisements with ambiguous metaphor techniques. Lastly, in order to produce successful advertising content, we expect to use the language technique of 'narrative metonymy' with warm feelings of humans, and acknowledge the lack of quantitative research and leave it as a task for the next research.

• Journal of Digital Convergence
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• v.17 no.8
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• pp.373-378
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• 2019

In various cultures and civilizations, artists are trying new ideas of reinterpreting the beauty of classic and redefining it in the ways of modern times rather than creating something new. In other words, modern cultural trend is creating a new culture by combining sensibilities of classic amid the flood of information with modern senses of artists. This study tries to combine various cultures an designs in accordance with this cultural change. Based on the features of expressing emotions of individuals and the world of impossible experiences from the short story 'When Buckwheat Flowers Bloom' of Lee Hyoseok, an incomplete area of consciousness which is at the border line of the polarized world divided by existence and absence is the area which creates a new culture by arousing readers' imagination as a potential world of thought. In addition, based on language from the short story, a researcher tries to utilize symbolic and imaginal beauties inside of that language as a material of design, and formative analysis them with the composition of proper words for visualization.

• The Transactions of the Korea Information Processing Society
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• v.13 no.3
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• pp.148-155
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• 2024

Despite the increasing importance of irony and sarcasm detection in the field of natural language processing, research on the Korean language is relatively scarce compared to other languages. This study aims to experiment with various models for irony detection in Korean text. The study conducted irony detection experiments using KoBERT, a BERT-based model, and ChatGPT. For KoBERT, two methods of additional training on sentiment data were applied (Transfer Learning and MultiTask Learning). Additionally, for ChatGPT, the Few-Shot Learning technique was applied by increasing the number of example sentences entered as prompts. The results of the experiments showed that the Transfer Learning and MultiTask Learning models, which were trained with additional sentiment data, outperformed the baseline model without additional sentiment data. On the other hand, ChatGPT exhibited significantly lower performance compared to KoBERT, and increasing the number of example sentences did not lead to a noticeable improvement in performance. In conclusion, this study suggests that a model based on KoBERT is more suitable for irony detection than ChatGPT, and it highlights the potential contribution of additional training on sentiment data to improve irony detection performance.

• Journal of the Ergonomics Society of Korea
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• v.17 no.3
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• pp.71-80
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• 1998

This study proposed a method to apply certain fuzzy-related Quality control concepts to design customer-oriented products considering user requirements and information starting with the product development stage. This approach showed how to define the importance level of design elements and how to Quantify complex subjective perception of products using the fuzzy linguistic rating method and quality function deployment concepts. Using this approach, various customer requirements could be interpreted and reflected on the early design phase of a new product. To validate the proposed method, an experiment was conducted for designing the shape of the beeper using 14 subjects and 10 commercial beeper products. Front area, width/length ratio, thickness, curve variance, weight, and display area were selected as design elements of the beeper. The results showed that among design elements, front area and weight are significantly related with the subjective perception of the products. Consequently, this study indicates that customer decision on product selection could be made by quantification of user perception for beeper products.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.11a
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• pp.431-434
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• 2012

본 논문에서는 소셜 빅데이터에 대한 심층적 언어분석을 통해 이슈를 탐지하고 모니터링하는 소셜위즈덤 시스템을 소개한다. 소셜위즈덤은 키워드의 단순 빈도 정보 외에도 이슈의 신규성, 중요성, 파급력, 관심도, 신뢰도 등을 수치화한 이슈성지수에 기반한 이슈성 측정이 가능하여 정확한 이슈탐지가 가능하다. 또한, 추가적인 정보로 단순 긍부정 분석이 아닌 17 개의 세부감성을 분석해서 제공하고 긍부정에 대한 호불호의 원인분석 정보도 제공하므로, 소셜미디어 분석에 기반한 깊은 인사이트를 제공하여 사용자의 의사결정에 많은 도움을 줄 수 있다.

• Proceedings of the Korea Information Processing Society Conference
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• 2004.05a
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• pp.385-388
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• 2004

인공지능분야에서의 온톨로지란 기본적인 개념의 규정과 개념들 사이의 관계를 표현한 용어들의 분류(classification)를 의미한다. 온톨로지를 만들기 위해서는 많은 온톨로지 관련 언어가 있다. 그 중 최근의 연구 방향은 DAML+OIL과 OWL로 작성된 온톨로지를 이용한 추론, 인텔리전트 서비스 분야이다. 본 논문에서는 웹 상의 미술 작품 온톨로지에 대해 기존의 키워드 매칭 검색 대신에 추론엔진을 이용한 시맨틱 기반의 확장된 검색 방법을 소개한다. 향후 연구는 퍼지 개념을 도입하여 기존의 결과 보다 정확한 검색 결과를 얻기 위한 연구를 할 것이다.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.191-206
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• 2022

Recently, it is a de-facto approach to utilize a pre-trained language model(PLM) to achieve the state-of-the-art performance for various natural language tasks(called downstream tasks) such as sentiment analysis and question answering. However, similar to any other machine learning method, PLM tends to depend on the data distribution seen during the training phase and shows worse performance on the unseen (Out-of-Distribution) domain. Due to the aforementioned reason, there have been many efforts to develop domain-specified PLM for various fields such as medical and legal industries. In this paper, we discuss the training of a finance domain-specified PLM for the Korean language and its applications. Our finance domain-specified PLM, KB-BERT, is trained on a carefully curated financial corpus that includes domain-specific documents such as financial reports. We provide extensive performance evaluation results on three natural language tasks, topic classification, sentiment analysis, and question answering. Compared to the state-of-the-art Korean PLM models such as KoELECTRA and KLUE-RoBERTa, KB-BERT shows comparable performance on general datasets based on common corpora like Wikipedia and news articles. Moreover, KB-BERT outperforms compared models on finance domain datasets that require finance-specific knowledge to solve given problems.

• Science of Emotion and Sensibility
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• v.18 no.1
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• pp.3-14
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• 2015

An ad endorser's gaze direction is a salient nonverbal cue that consumers use in responding to advertisements. The gaze direction influences consumers' social perceptions (e.g., attractiveness, credibility) of the endorser and advertising effectiveness (e.g., advertising attitudes, brand attitudes). Especially, the cerebral emotional asymmetry hypothesis suggests that an ad endorser's left-averted gaze can produce more positive social perceptions and advertising effectiveness than the right-averted gaze for right-handed consumers. This study examined the effects of three gaze directions (direct, left-averted and right-averted gaze directions) of unknown female ad endorser on Korean males' advertising responses (attractiveness-, credibility- and ad-effectiveness-related responses), using online experimental method. The results indicated that the ad endorser's direct gaze was more likely to increase both positive (correspondence bias) and negative (suspicion, deceptiveness) social perceptions of her than the right-averted gaze. The direct gaze also created more positive advertising effectiveness (advertising attitudes) than the right-averted gaze. However, the study failed to find consistent differences in responses between left-averted gaze and either direct or right-averted gaze.