• Science of Emotion and Sensibility
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• v.18 no.1
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• pp.103-110
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• 2015

Sentiment lexicon is an essential element for expressing sentiment on a text or recognizing sentiment from a text. We propose a graph-based semi-supervised learning method to construct a sentiment dictionary as sentiment lexicon set. In particular, we focus on the construction of domain-specific sentiment dictionary. The proposed method makes up a graph according to lexicons and proximity among lexicons, and sentiments of some lexicons which already know their sentiment values are propagated throughout all of the lexicons on the graph. There are two typical types of the sentiment lexicon, sentiment words and sentiment phrase, and we construct a sentiment dictionary by creating each graph of them and infer sentiment of all sentiment lexicons. In order to verify our proposed method, we constructed a sentiment dictionary specific to the movie domain, and conducted sentiment classification experiments with it. As a result, it have been shown that the classification performance using the sentiment dictionary is better than the other using typical general-purpose sentiment dictionary.

• Smart Media Journal
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• v.5 no.1
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• pp.61-68
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• 2016

According to increasing SNS users and developing smart devices like smart phone and tablet PC recently, many techniques to classify user emotions with social network information are researching briskly. The use emotion classification stands for distinguishing its emotion with text and images listed on his/her SNS. This paper suggests a method to classify user emotions through sampling a value of a representative figure on a trigonometrical function, a representative adjective on text, and a canny algorithm on images. The sampling representative adjective on text is selected as one of high frequency in the samplings and measured values of positive-negative by SentiWordNet. Figures sampled on images are selected as the representative in figures; triangle, quadrangle, and circle as well as classified user emotions by measuring pleasure-unpleased values as a type of figures and inclines. Finally, this is re-defined as x-y graph that represents pleasure-unpleased and positive-negative values with wheel of emotions by Plutchik. Also, we are anticipating for applying user-customized service through classifying user emotions on wheel of emotions by Plutchik that is redefined the representative adjectives and figures.

• Science of Emotion and Sensibility
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• v.26 no.3
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• pp.15-28
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• 2023

This study examined the affective representation and response consistency among individuals using affective videos, a naturalistic stimulus inducing emotional experiences most similar to those in daily life. In this study, multidimensional scaling was conducted to investigate whether the various affective representations induced through video stimuli are located in the core affect dimensions. A cross-participant classification analysis was also performed to verify whether the video stimuli are well classified. Additionally, the newly developed intersubject correlation analysis was conducted to assess the consistency of affective representations across participant responses. Multidimensional scaling revealed that the video stimuli are represented well in the valence dimension, partially supporting Russell (1980)'s core affect theory. The classification results showed that affective conditions were successfully classified across participant responses. Moreover, the intersubject correlation analysis showed that the consistency of affective representations to video stimuli differed with respect to the condition. This study suggests that the affective representations and consistency of individual responses to affective videos varied across different affective conditions.

• Journal of Korea Game Society
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• v.10 no.4
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• pp.15-22
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• 2010

The purpose of this research is to analyze players' emotion pattern for conducting a quest in Role Playing Game(RPG). We have rebuilt up the action and content of gameplay related to category to set up five action classes of game players based on the literature review about the human behavior classification. Moreover, Mabinogi game includes the composition of various quests by story-centered expanse. We classified the quest structure of the tutorial mode, initial state, of its game into the cognitive action. We build the model of the correlation between cognitive behavior patterns of gameplay and emotions derived from targeting ten novices. The result of this research reveals that gameplayers' stimulus levels are identified to emotion pattern. It is enable to grope to concrete the design of the quest and the level in a specified state. Moreover, players' emotion variation is indicated to the type of expression of fun elements. We expect to use a device to induce the curiousness and the challenge for conducting the higher goal of game in the whole.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.4
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• pp.11-19
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• 2023

The paper proposes a smart mirror system that recommends fragrances based on user emotion analysis. This paper combines natural language processing techniques such as embedding techniques (CounterVectorizer and TF-IDF) and machine learning classification models (DecisionTree, SVM, RandomForest, SGD Classifier) to build a model and compares the results. After the comparison, the paper constructs a personal emotion-based fragrance recommendation mirror model based on the SVM and word embedding pipeline-based emotion classifier model with the highest performance. The proposed system implements a personalized fragrance recommendation mirror based on emotion analysis, providing web services using the Flask web framework. This paper uses the Google Speech Cloud API to recognize users' voices and use speech-to-text (STT) to convert voice-transcribed text data. The proposed system provides users with information about weather, humidity, location, quotes, time, and schedule management.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.5 no.1
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• pp.45-51
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• 2012

In this paper, it's a system which recognize the user's emotions after obtaining the biological informations(pulse sensor, blood pressure sensor, blood sugar sensor etc.) about user's bio informations through wireless sensors in accordance of previously collected informations about user's stress index and classification the Colors & Music. This system collects the inputs, saves in the database and finally, classifies emotions according to the stress quotient by using multiple SVM(Support Vector Machine) algorithm. The experiment of multiple SVM algorithm was conducted by using 2,000 data sets. The experiment has approximately 87.7% accuracy.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.342-351
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• 2000

The paper is concerned about the discovery of new physics of the old oriental philosophy of the yin-Yang '||'&'||' five elements. the physical properties of Five Elements are defined, similarly as in thermodynamics, as five different characteristic state in a cyclic system of nature or a human body. Wood is defined as "warm and soft", Fire as "hot and dispersive", Earth as "agglomerating and sticky", Metal as "tensile and crystallizing", and Water as "cool and slippery" state, respectively. Based on the physics of Five Elements and Qi channel theory, five different constitution classification s are made according to the shape of human face, such as long, inverse triangle, circle, square, and triangle geometry, respectively.Since the constitution implies the relative size or strength of 5 major organs, this theory can be applies successfully to the prediction of the susceptibility to specific diseases as well as the analyses of personal character such as emotion and sensibility. The specific character is analyzed with four different aspects; that is, the first and second are caused by the positive and negative side of the strongest organ, the third character by determined the weakest organ, and finally the fourth by the abnormal psychology due to serious illness.bnormal psychology due to serious illness.

• Journal of IKEEE
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• v.22 no.3
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• pp.816-821
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• 2018

Recently, machine learning algorithms based on artificial neural networks started to be used widely as classifiers in the field of EEG research for emotion analysis and disease diagnosis. When a machine learning model is used to classify EEG data, if training data is composed of only data having similar characteristics, classification performance may be deteriorated when applied to data of another group. In this paper, we propose a method to construct training data set by selecting several groups of data using semi-supervised learning algorithm to improve these problems. We then compared the performance of the two models by training the model with a training data set consisting of data with similar characteristics to the training data set constructed using the proposed method.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1998.11a
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• pp.30-39
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• 1998

음양오행의 오행에 해당하는 화, 수 목, 금, 수를 원동력의 물리적 개념에 입각하여 5가지의 성격을 가진 에너지 또는 힘으로 정의하였다. 이 정의에 기초하여 사람의 얼굴 형상, 기본적인 성격, 병든 성격 등 체질, 감정, 건강에 관계된 100개 이상의 문항을 가진 설문지를 완성하였다. 설문지의 구성은 오행의 화, 수, 상, 금, 수 5 분야와 더불어 생명력을 나타내는 상화를 포함 6개 분야로 구성되었으며 각 분야에는 각각 20여 개의 문항을 만들었다 구체적으로 각 오행에 해당하는 장부가 크거나 좋을 때 나타날 수 있는 기본적인 성격과 부정적인 성격을 파악하는 질문으로 10문제를 만들었으며 다른 10문제에는 해당장부가 나쁠 때 나타날 수 있는 육체적/정신적 증상을 묻는 문제를 제시하였다. 그리고 마지막 2∼3문제는 정신적으로 광적인 증세를 묻는 총 130여 문항으로 구성하였다 설문지 평가 결과 스스로 성격진단, 섭생이나 인, 의, 예, 지 실 덕목의 연관관계, 직장에서 인적 자원 배치와 함께 산업안전과의 연관관계 등을 구체적으로 나타내었다. 제한된 평가결과 비교적 사람의 체질이나 성격 등을 잘 파악하였으나 교육이나 유전 또는 사주에 의한 특성이 강할 때는 예외성을 나타내는 것으로 생각되었다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.3
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• pp.186-191
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• 2015

Hand gesture is the most common tool used to interact with and control various electronic devices. In this paper, we propose a novel hand gesture recognition method using fuzzy logic based classification with a new type of sensor array. In some cases, feature patterns of hand gesture signals cannot be uniquely distinguished and recognized when people perform the same gesture in different ways. Moreover, differences in the hand shape and skeletal articulation of the arm influence to the process. Manifold features were extracted, and efficient features, which make gestures distinguishable, were selected. However, there exist similar feature patterns across different hand gestures, and fuzzy logic is applied to classify them. Fuzzy rules are defined based on the many feature patterns of the input signal. An adaptive neural fuzzy inference system was used to generate fuzzy rules automatically for classifying hand gestures using low number of feature patterns as input. In addition, emotion expression was conducted after the hand gesture recognition for resultant human-robot interaction. Our proposed method was tested with many hand gesture datasets and validated with different evaluation metrics. Experimental results show that our method detects more hand gestures as compared to the other existing methods with robust hand gesture recognition and corresponding emotion expressions, in real time.