• Proceedings of the Korean Operations and Management Science Society Conference
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• 2000.04a
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• pp.413-416
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• 2000

현재 소비자의 광고 효과 측정에 대한 연구는 정보 처리 모형에 근거한 인지 반응 연구와 주관적인 감성 반응 연구가 주를 이루고 있다. 이에 본 연구에서는 TV 광고에 대한 광고 효과를 인지와 감성적 부분으로 분류하여 해석한 Shimp(1981)의 모델을 기초로하여 각각의 뇌파의 반응을 측정하였고, 동시에 광고에 대한 감성형용사, 선호도, 구매 욕구를 통한 주관적 평가를 실시하였다. 그 결과 정보전달형 광고와 감성자극형 광고에 있어 뇌파 활성도, 감성형용사, 선호도의 차이를 나타냈다. 본 결과는 광고에 대한 소비자의 반응을 정량적인 방법으로 측정하여, 광고 효과 파악을 위한 새로운 모델의 가능성을 제시하였다는데 의의가 있다.

• Proceedings of the KAIS Fall Conference
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• 2005.05a
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• pp.111-114
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• 2005

현재 휴대폰은 대중화되고 있으며, 로봇기술 또한 각광 받고 있다. 그래서 우리는 로봇기술과 휴대폰 기술을 접목한 RCP(Robotic Cellular Phone)를 구현하려 한다. RCP를 구성하기 위해서 휴대폰의 움직임을 구현, 외부환경 및 RCP 자신의 상태인식 기능 그리고 사용자의 감성을 유발할 수 있는 감성유발엔진 및 감성평가모델의 군축이 필요하다. 본 연구에서는 감성평가모델의 개발을 위하여 음악과 진동 자극을 주어 생체신호 HRV와 GSR을 측정하여 정량적인 데이터를 수집, 특정감성을 평가하였다. 감성을 평가함에 있어서 개인의 차이가 발생하기 때문에 개개인의 표준화 (Normalize)가 필요하게 되었다. 표준화를 위하여 IAPS영상을 활용한 결과 우리가 얻고자 하는 감성의 변화에 대한 판단을 할 수 있음으로 감성의 신호 모델을 유추할 수 있었다.

• Science of Emotion and Sensibility
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• v.11 no.1
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• pp.69-80
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• 2008

The scheme to approach emotional design developed in various way of research without defining criterion of emotional way. A aim of this research to derive a new way of approaching system and construct the process in emotional design. In first experiments, analyze meaning of important factors in cooking kits to construct the model of emotional approaching system by the analysis of quantification theory type 3. This shows that four emotional factors as shape, atmosphere, functional matter, information are deeply related with emotional thinking and design. Consequently, the way of emotional approaching in cooking kit have several conditions essentially as following these; 1.Is it have functional advantages to cook? 2. Is it good looking in shape? 3. Is it possible to make some of mood on cooking? 4. How much information of cook we get in? These conditions were classified in detail to establish emotional design system.

• The Journal of the Korea Contents Association
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• v.17 no.3
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• pp.421-430
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• 2017

In this paper, research results on the change of music emotion are described. Our gaol was to provide a method of changing music emotion by a human user. Then we tried to find a way of transforming the contents of the original music into the music whose emotion is similar with the changed emotion. For the purpose, a method of changing the emotion of playing music on two-dimensional plan was describe. Then the original music should be transformed into the music which emotion would be equal to the changed emotion. As the first step a method of deciding which music factors and how much should be changed was presented. Finally the experimental method of editing by sound editor for changing the emotion was described. There are so many research results on the recognition of music emotion. But the try of changing the music emotion is very rare. So this paper would open another way of doing research on music emotion field.

• Journal of the Korea Society of Computer and Information
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• v.18 no.5
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• pp.43-52
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• 2013

In recent years, a large amount of music content is distributed in the Internet environment. In order to retrieve the music content effectively that user want, various studies have been carried out. Especially, it is also actively developing music recommendation system combining emotion model with MIR(Music Information Retrieval) studies. However, in these studies, there are several drawbacks. First, structure of emotion model that was used is simple. Second, because the emotion model has not designed for Korean language, there is limit to process the semantic of emotional words expressed with Korean. In this paper, through extending the existing emotion model, we propose a new emotion model KOREM(KORean Emotional Model) based on Korean. And also, we design and implement ontology using emotion model proposed. Through them, sorting, storage and retrieval of music content described with various emotional expression are available.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1784-1789
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• 2021

Korean sentiment classification task is used in real-world services such as chatbots and analysis of user's purchase reviews. And due to the development of deep learning technology, neural network models with high performance are being applied. However, the neural network model is not easy to interpret what the input sentences are predicting due to which words, and recently, model interpretation methods for interpreting these neural network models have been popularly proposed. In this paper, we used the LIME algorithm among the model interpretation methods to interpret which of the words in the input sentences of the models learned with the korean sentiment classification dataset. As a result, the interpretation of the Bi-LSTM model with 85.24% performance included 25,283 words, but 84.20% of the transformer model with relatively low performance showed that the transformer model was more reliable than the Bi-LSTM model because it contains 26,447 words.

• The Transactions of the Korea Information Processing Society
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• v.13 no.5
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• pp.209-216
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• 2024

Real estate market prices are determined by various factors, including macroeconomic variables, as well as the influence of a variety of unstructured text data such as news articles and social media. News articles are a crucial factor in predicting real estate transaction prices as they reflect the economic sentiment of the public. This study utilizes sentiment analysis on news articles to generate a News Sentiment Index score, which is then seamlessly integrated into a real estate price prediction model. To calculate the sentiment index, the content of the articles is first summarized. Then, using AI, the summaries are categorized into positive, negative, and neutral sentiments, and a total score is calculated. This score is then applied to the real estate price prediction model. The models used for real estate price prediction include the Multi-head attention LSTM model and the Vector Auto Regression model. The LSTM prediction model, without applying the News Sentiment Index (NSI), showed Root Mean Square Error (RMSE) values of 0.60, 0.872, and 1.117 for the 1-month, 2-month, and 3-month forecasts, respectively. With the NSI applied, the RMSE values were reduced to 0.40, 0.724, and 1.03 for the same forecast periods. Similarly, the VAR prediction model without the NSI showed RMSE values of 1.6484, 0.6254, and 0.9220 for the 1-month, 2-month, and 3-month forecasts, respectively, while applying the NSI led to RMSE values of 1.1315, 0.3413, and 1.6227 for these periods. These results demonstrate the effectiveness of the proposed model in predicting apartment transaction price index and its ability to forecast real estate market price fluctuations that reflect socio-economic trends.

• Journal of Science Education
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• v.34 no.2
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• pp.185-192
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• 2010

The purpose of this study was to develope the negative-emotion prediction model by hormonal changes during the scientific inquiry. For this study, biological classification task was developed that are suitable for comprehensive scientific inquiry. Forty-seven 2nd grade secondary school students (boy 18, girl 29) were participated in this study. The students are healthy for measure hormonal changes. The students performed the feathers classification task individually. Before and after the task, the strength of negative emotion was measured using adjective emotion check lists and they extracted their saliva sample for salivary hormone analysis. The results of this study, student's change of negative emotion during the feathers classification process was significant positive correlation(R=0.39, P<0.001) with student's salivary cortisol concentration. According to this results, we developed the negative emotion prediction model by salivary cortisol changes.

• Science of Emotion and Sensibility
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• v.2 no.2
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• pp.67-74
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• 1999

본 연구는 실제 현장에서 적용할 수 있는 보다 구체적인 감성 데이터를 제공하기 위한 시도로서, 메이크업의 주요한 색채특성을 평가변인으로 하여 칼라 시뮬레이션 실험 및 분석을 실시하여, 최종적으로 색채감성 분석기법에 의한 이미지 유형별 예측모델을 작성하였다. 그 결과, $\ulcorner$품위있는.귀족적인$\lrcorner$, $\ulcorner$깔끔한.여성스러운$\lrcorner$, $\ulcorner$강렬한.도발적인$\lrcorner$, $\ulcorner$캐주얼한.경쾌한$\lrcorner$, $\ulcorner$수수한.부드러운$\lrcorner$의 5가지 이미지유형이 추출되었고, 이미지유형별로 이미지와 색채특성간의 정량적 예측모델을 작성한 후, 그 결과를 토대로 이미지유형별 색채팔레트를 제시하였다.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1999.11a
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• pp.324-329
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• 1999

본 연구는 실제 현장에서 적용할 수 있는 보다 구체적인 감성 데이터를 제공하기 위한 시도로서, 메이크업의 주요한 색채특성을 정가변인으로 하여 칼라 시뮬레이션 실험을 실시한 후, 색채감성 분석기법에 의한 이미지유형별 예측모델을 작성하였다. 그 결과, $\ulcorner$품위있는ㆍ귀족적인$\lrcorner$, $\ulcorner$깔끔한ㆍ여성스러운$\lrcorner$, $\ulcorner$강렬한ㆍ도발적인$\lrcorner$, $\ulcorner$캐주얼한ㆍ경쾌한$\lrcorner$, $\ulcorner$수수한ㆍ부드러운$\lrcorner$ 의 5가지 이미지유형이 추출되었고, 이미지유형별로 이미지와 색채특성간의 정량적 예측모델을 작성한 후, 그 결과를 토대로 이미지유형별 색채팔레트를 제시하였다.