• International journal of advanced smart convergence
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• v.9 no.1
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• pp.141-153
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• 2020

This study aims to understand the antecedents and consequences of flow experience in online movie information sharing behavior of young Chinese moviegoers residing in Korea to explore a potential market. We followed the Stimulus-Organism-Response (S-O-R) theory and flow theory approaches for developing measures of constructs and investigated previous related studies. This study collected 186 data from Chinses students who attend Korean university. Statistical analysis revealed that information seeking behavior and telepresence are related to online flow experience. In addition, the online flow experience affected consumer satisfaction and information sharing behavior. Flow experience also has been predicted the mediation effect between stimulus information seeking behavior, telepresence and satisfaction and information sharing behavior. Our research findings offer insights for marketers in the movie distribution business who are interested in a better understanding of the behaviors of Chinese moviegoers residing in Korea

• Proceedings of the Korean Society for Language and Information Conference
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• 2007.11a
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• pp.481-488
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• 2007

In this paper, we propose a method to classify movie review documents into positive or negative opinions. There are several approaches to classify documents. The previous studies, however, used only a single classifier for the classification task. We describe a multiple classifier for the review document classification task. The method consists of three classifiers based on SVMs, ME and score calculation. We apply two voting methods and SVMs to the integration process of single classifiers. The integrated methods improved the accuracy as compared with the three single classifiers. The experimental results show the effectiveness of our method.

• The Research Journal of the Costume Culture
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• v.5 no.2
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• pp.285-295
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• 1997

This dissertation aims to study a role and importance of clothing as a visual transmission system, with investigating the system and structure of a pragmatics in a cinema costume and analyzing what the meaning of a pragmatics is, depending on the circumstance on the circumstance on the basis of pragmatics. It examines as an objective the clothes of Scarlett, a heroine in 'Gone with the Wind's film originated from the novel written by Margaret Mitchell. As a result of this study, the movie costumes demonstrate a purposed transmission medium as a describing tool governing comprehensive circumstances in the process of drama. The costume plays a significant role in delivering a meaning of a movie showing historical backgrounds, social situations, and psychological description, status, characteristics, tastes of characters by means of their costumes in the movie.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.208-211
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• 2004

Hundred numbers of Special effects in animation and movie are essentionally used. Owing to the rapidly growth of Production method and special techniques, we can produce a real effect such as real scene. The aim of special effect is to generate refined scene, which we can't distinguish one from another. In this paper, New trend of special effects in animation and movie are compared and investigated the extension methods. And also we prospect the development direction of special effect.

• Journal of Digital Convergence
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• v.8 no.2
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• pp.103-114
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• 2010

People generally focus on the supply side when conducting a study on the movie industry. However, to understand the movie industry better, one needs to analyze both sides - the demand and supply of movies. This paper analyzes demand-side factors that have long been taken for granted in Korea's movie industry. The study used data for 1991~2008 on the following demand-factors : the average ticket prices, the number of working days and hours, the average personal income, the number of spectators for the two major professional sports, cable TV, the number of movies released each year and the number of movie screens. This study shows that ticket prices do not conform to the law of demand. According to the law of demand, increasing price leads to a decline in demand. However, in reality, the number of viewers went up along with ticket prices. The study found that demand for movies was correlated to income levels and leisure time. An increase in the number of leisure hours and income levels pushed up demand. Contrary to general belief, a growth in the availability of substitutes, such as professional sports(soccer and baseball), did not result in a fall in demand for movies. The audiences for both sports and movies grew simultaneously as the amount of leisure time increased. Contrary to the general expectations that more diversified genres of movies will draw larger audiences by satisfying different individual tastes, the diversification had little impact, but the number of movie screens was positively correlated with audience size. In sum, changes in ticket prices and the quantity of substitutes had little influence on demand in the movie industry. Rather, it was the supply side of the industry that induced demand.

• Journal of Power System Engineering
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• v.17 no.6
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• pp.40-46
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• 2013

This paper describes the suggestion of the special seat with the auxiliary plastic member for movie theater chair. In the previous paper, we have reported on the development of foaming sponge seat with the auxiliary spring member. And we have confirmed that it was more effective on vibration transfer than the chair seat of foaming sponge only. In this study, we have examined the major design parameters needed in the development of a foaming sponge seat in which the mesh type plastic member are inserted to improve the vibration transfer effect of a chair seat. By applying experimentation to the prototype as well as the experimental modal analysis method, we made sure that the effect of the vibration transfer could be improved through the use of a mesh type plastic member as similar as the auxiliary spring member.

• Journal of the Korea Society of Computer and Information
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• v.24 no.1
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• pp.49-55
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• 2019

The character dialogue created by AI is unnatural when compared with human-made dialogue, and it can not reveal the character's personality properly in spite of remarkable development of AI. The purpose of this paper is to classify characters through the linguistic style and to investigate the relation of the specific linguistic style with the personality. We analyzed the dialogues of 92 characters selected from total 60 movies categorized four movie genres, such as romantic comedy, action, comedy and horror/thriller, using Linguistic Inquiry and Word Count (LIWC), a text analysis software. As a result, we confirmed that there is a unique language style according to genre. Especially, we could find that the emotional tone than analytical thinking are two important features to classify. They were analyzed as very important features for classification as the precision and recall is over 78% for romantic comedy and action. However, the precision and recall were 66% and 50% for comedy and horror/thriller. Their impact on classification was less than romantic comedy and action genre. The characters of romantic comedy deal with the affection between men and women using a very high value of emotional tone than analytical thinking. The characters of action genre who need rational judgment to perform mission have much greater analytical thinking than emotional tone. Additionally, in the case of comedy and horror/thriller, we analyzed that they have many kinds of characters and that characters often change their personalities in the story.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.1
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• pp.25-40
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• 2023

Recommendation systems are frequently used by users to generate intelligent automatic decisions. In the study of movie recommendation system, the existing approach uses largely collaboration and content-based filtering techniques. Collaborative filtering considers user similarity, while content-based filtering focuses on the activity of a single user. Also, mixed filtering approaches that combine collaborative filtering and content-based filtering are being used to compensate for each other's limitations. Recently, several AI-based similarity techniques have been used to find similarities between users to provide better recommendation services. This paper aims to provide the prospective expansion by deriving possible solutions through the analysis of various existing movie recommendation systems and their challenges.

• The Journal of the Korea Contents Association
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• v.11 no.11
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• pp.130-136
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• 2011

This study analyzed and compared Dong-a Il-bo, a new material, based on the result of analysis of movie commercials on Mae-il Shin-bo from the previous study. Although we could not analyze precisely them in regard to their form, there are differences between them in terms of where they show movie commercials and how large their movie commercials are. However, in terms of the content, the characteristics of movies in the 1930s correspond with the result of the study that analyzed Mae-Il Shin-Bo. As Mae-Il Shin-Bo was actually a organ of the Japanese Government-General of Korea, and Dong-A Il-Bo was a representative of private newspapers, our comparative study actually covered almost all materials on the movies of the 1930s, considering repeating movie commercials. Based on the results of this study, we can learn more precisely the characteristics of the movies in the 1930s.

• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.833-842
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• 2020

Global platforms such as Netflix, Amazon, and YouTube have developed a precise recommendation system based on various information from large set of customers and many of the items recommended here are leading to actual purchases. In this paper, a cluster analysis was conducted according to the attribute of the content, expecting that there would be a difference in user preferences according to the attribute of the recommended content. Gower distance was used for use regardless of the type of variables. In this paper, using the data of movie rating site 'The Movie Dataset', the users were grouped hierarchically and recommended movies based on genre, director and actor variables. To evaluate the recommended systems proposed, user group was divided into train set and test set to examine the precision. The results showed that proposed algorithms have far higher precision than UBCF.