• Title, Summary, Keyword: 자극기반 의사결정

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An empirical study on the roles of attitudes and attitude strength in stimulus-based decision-making (자극기반 의사결정과정에서 태도와 태도강도의 역할에 관한 실증연구)

  • Beom, Sang-Kyu;Song, Kyun-Suk
    • Journal of the Korean Data and Information Science Society
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    • v.20 no.3
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    • pp.563-575
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    • 2009
  • This research has found logical data directly influencing forming consideration set and attitude and attitude strength under the choosing situation based on memory-base proposed by Priester et. al (2004). We've examined the possibility of model extension through physical salient strength according to the location of product display as an external stimulate factor and attitude and attitude strength, consideration set and role on variable choice. Especially, this research practically proposed the method measuring directly the attitude on behavior instead of seeing the intension of behavior or behavior by measuring the behavior itself based on existing experiment methods and applied logistics regression analysis. In conclusion, this research confirmed the possibility of generalization of this model by verifying appropriateness through logical background and actual analysis based on stimulus-base proposed model characters as an integrated model relation between attitude in stimulus-based relation and decision-making.

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A Study on Image Sensibility Evaluation (이미지의 감성평가에 대한 연구)

  • Lyu, Ki-Gon;Sun, Dong-Eun;Han, Jung-Soo;Kim, Hyeon-Cheol
    • Proceedings of the Korea Information Processing Society Conference
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    • pp.1697-1698
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    • 2013
  • 정보처리 기술이 발전함에 따라 정보에 대한 접근과 소통은 더욱 빠르고 편리하게 되었고, 동시에 사용자의 정보에 대한 요구 또한 세분화되고 다양해지면서, 이러한 다양한 요구에 대응하기 위해서 사용자의 경험과 소통하여 인지과정에 영향을 줄 수 있는 감성이 중요하게 인식되고 있다. 감성은 동일한 외부자극에 대해 개인의 경험, 환경 등에 따라 다르게 나타나기 때문에 객관적으로 측정하기가 어렵지만, 외부자극에 대해 반사적이고 직관적으로 발생하여 의사결정 과정에 지속적으로 영향을 주기 때문에 사용자의 경험과 소통하여 사용자의 요구를 이해할 수 있는 정보를 제공한다. 본 논문에서는 이미지 공유 사이트를 이용하여 이미지라는 외부자극에 대해 사용자들이 느낀 어휘들을 수집하고 긍정과 부정 감성을 분석하여 어휘를 기반으로 이미지의 감성을 측정하고 평가하였다.

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Design and Implementation of Web-Based Career Guidance System Applied Multiple Intelligences Theory (다중지능이론을 적용한 웹기반 진로안내시스템의 설계 및 구현)

  • Min, Hang-Gee;Lee, Jae-Mu
    • Journal of The Korean Association of Information Education
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    • v.11 no.3
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    • pp.349-358
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    • 2007
  • This study is to develop a web-based career guidance system to be a help making a decision on one's occupation, which is important for a person's life. As career development education for higher grades of elementary school aims at providing basic knowledge necessary for career choice and forming a basic attitude toward occupation and values, it is desirable to carry out the guidance of a variety of occupations on the basis of personal interest and aptitude of individual students. Previously, however, most studies have remained at the level where simply test results are notified. Therefore, the study administered a career development test fit for higher grades of elementary school who are at the stage of potential career choice and developed a web-based career guidance system in which suitable occupation types are advised of based on the results. Beyond notifying test results, the developed career guidance system presents 3 excellent intelligences, rather than converting test results into scores. Thus, it is expected that the system will help students understand their areas of excellent intelligence, efficiently study related occupation types and duties, and learn to have awareness and make a better decision in relation to their career.

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Bio-mimetic Recognition of Action Sequence using Unsupervised Learning (비지도 학습을 이용한 생체 모방 동작 인지 기반의 동작 순서 인식)

  • Kim, Jin Ok
    • Journal of Internet Computing and Services
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    • v.15 no.4
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    • pp.9-20
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    • 2014
  • Making good predictions about the outcome of one's actions would seem to be essential in the context of social interaction and decision-making. This paper proposes a computational model for learning articulated motion patterns for action recognition, which mimics biological-inspired visual perception processing of human brain. Developed model of cortical architecture for the unsupervised learning of motion sequence, builds upon neurophysiological knowledge about the cortical sites such as IT, MT, STS and specific neuronal representation which contribute to articulated motion perception. Experiments show how the model automatically selects significant motion patterns as well as meaningful static snapshot categories from continuous video input. Such key poses correspond to articulated postures which are utilized in probing the trained network to impose implied motion perception from static views. We also present how sequence selective representations are learned in STS by fusing snapshot and motion input and how learned feedback connections enable making predictions about future input sequence. Network simulations demonstrate the computational capacity of the proposed model for motion recognition.

The Intelligent Determination Model of Audience Emotion for Implementing Personalized Exhibition (개인화 전시 서비스 구현을 위한 지능형 관객 감정 판단 모형)

  • Jung, Min-Kyu;Kim, Jae-Kyeong
    • Journal of Intelligence and Information Systems
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    • v.18 no.1
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    • pp.39-57
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    • 2012
  • Recently, due to the introduction of high-tech equipment in interactive exhibits, many people's attention has been concentrated on Interactive exhibits that can double the exhibition effect through the interaction with the audience. In addition, it is also possible to measure a variety of audience reaction in the interactive exhibition. Among various audience reactions, this research uses the change of the facial features that can be collected in an interactive exhibition space. This research develops an artificial neural network-based prediction model to predict the response of the audience by measuring the change of the facial features when the audience is given stimulation from the non-excited state. To present the emotion state of the audience, this research uses a Valence-Arousal model. So, this research suggests an overall framework composed of the following six steps. The first step is a step of collecting data for modeling. The data was collected from people participated in the 2012 Seoul DMC Culture Open, and the collected data was used for the experiments. The second step extracts 64 facial features from the collected data and compensates the facial feature values. The third step generates independent and dependent variables of an artificial neural network model. The fourth step extracts the independent variable that affects the dependent variable using the statistical technique. The fifth step builds an artificial neural network model and performs a learning process using train set and test set. Finally the last sixth step is to validate the prediction performance of artificial neural network model using the validation data set. The proposed model is compared with statistical predictive model to see whether it had better performance or not. As a result, although the data set in this experiment had much noise, the proposed model showed better results when the model was compared with multiple regression analysis model. If the prediction model of audience reaction was used in the real exhibition, it will be able to provide countermeasures and services appropriate to the audience's reaction viewing the exhibits. Specifically, if the arousal of audience about Exhibits is low, Action to increase arousal of the audience will be taken. For instance, we recommend the audience another preferred contents or using a light or sound to focus on these exhibits. In other words, when planning future exhibitions, planning the exhibition to satisfy various audience preferences would be possible. And it is expected to foster a personalized environment to concentrate on the exhibits. But, the proposed model in this research still shows the low prediction accuracy. The cause is in some parts as follows : First, the data covers diverse visitors of real exhibitions, so it was difficult to control the optimized experimental environment. So, the collected data has much noise, and it would results a lower accuracy. In further research, the data collection will be conducted in a more optimized experimental environment. The further research to increase the accuracy of the predictions of the model will be conducted. Second, using changes of facial expression only is thought to be not enough to extract audience emotions. If facial expression is combined with other responses, such as the sound, audience behavior, it would result a better result.