• Journal of Korea Multimedia Society
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• v.18 no.9
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• pp.1068-1082
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• 2015

Due to the rapid advancement of the mobile technology, smart phones have been widely used in the current society. This lead to an easier way to retrieve video contents using web and mobile services. However, it is not a trivial problem to retrieve particular video contents based on users' specific preferences. The current movie recommendation system is based on the users' preference information. However, this system does not consider any emotional means or perspectives in each movie, which results in the dissatisfaction of user's emotional requirements. In order to address users' preferences and emotional requirements, this research proposes a movie recommendation technology to represent a movie's emotion and its associations. The proposed approach contains the development of emotion ontology by representing the relationship between the emotion and the concepts which cause emotional effects. Based on the current movie metadata ontology, this research also developed movie-emotion ontology based on the representation of the metadata related to the emotion. The proposed movie recommendation method recommends the movie by using movie-emotion ontology based on the emotion knowledge. Using this proposed approach, the user will be able to get the list of movies based on their preferences and emotional requirements.

• Journal of information and communication convergence engineering
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• v.15 no.1
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• pp.43-48
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• 2017

Movie ratings are crucial for recommendation engines that track the behavior of all users and utilize the information to suggest items the users might like. It is intuitively appealing that information about the viewing preferences in terms of movie genres is sufficient for predicting a genre of an unlabeled movie. In order to predict movie genres, we treat ratings as a feature vector, apply a Bernoulli event model to estimate the likelihood of a movie being assigned a certain genre, and evaluate the posterior probability of the genre of a given movie by using the Bayes rule. The goal of the proposed technique is to efficiently use movie ratings for the task of predicting movie genres. In our approach, we attempted to answer the question: "Given the set of users who watched a movie, is it possible to predict the genre of a movie on the basis of its ratings?" The simulation results with MovieLens 1M data demonstrated the efficiency and accuracy of the proposed technique, achieving an 83.8% prediction rate for exact prediction and 84.8% when including correlated genres.

• Journal of Information Technology Services
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• v.16 no.3
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• pp.167-183
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• 2017

The rapid growth of information technology and mobile service platforms, i.e., internet, google, and facebook, etc. has led the abundance of data. Due to this environment, the world is now facing a revolution in the process that data is searched, collected, stored, and shared. Abundance of data gives us several opportunities to knowledge discovery and data mining techniques. In recent years, data mining methods as a solution to discovery and extraction of available knowledge in database has been more popular in e-commerce service fields such as, in particular, movie recommendation. However, most of the classification approaches for predicting the movie popularity have used only several types of information of the movie such as actor, director, rating score, language and countries etc. In this study, we propose a classification-based support vector machine (SVM) model for predicting the movie popularity based on movie's genre data and social network data. Social network analysis (SNA) is used for improving the classification accuracy. This study builds the movies' network (one mode network) based on initial data which is a two mode network as user-to-movie network. For the proposed method we computed degree centrality, betweenness centrality, closeness centrality, and eigenvector centrality as centrality measures in movie's network. Those four centrality values and movies' genre data were used to classify the movie popularity in this study. The logistic regression, neural network, $na{\ddot{i}}ve$ Bayes classifier, and decision tree as benchmarking models for movie popularity classification were also used for comparison with the performance of our proposed model. To assess the classifier's performance accuracy this study used MovieLens data as an open database. Our empirical results indicate that our proposed model with movie's genre and centrality data has by approximately 0% higher accuracy than other classification models with only movie's genre data. The implications of our results show that our proposed model can be used for improving movie popularity classification accuracy.

• 한국어정보학회:학술대회논문집
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• 2016.10a
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• pp.249-251
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• 2016

다중 화자 대화 시스템에서, 시스템의 입장에서 어느 시점에 참여해야하는지를 아는 것은 중요하다. 이러한 참여 모델을 구축함에 있어서 본 연구에서는 다수의 화자가 대화에 참여하는 영화 대본으로 구축된 MovieDic 말뭉치를 사용하였다. 구축에 필요한 자질로써 의문사, 호칭, 명사, 어휘 등을 사용하였고, 훈련 알고리즘으로는 Maximum Entropy Classifier를 사용하였다. 실험 결과 53.34%의 정확도를 기록하였으며, 맥락 자질의 추가로 정확도 개선을 기대할 수 있다.

• International Journal of Advanced Culture Technology
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• v.10 no.2
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• pp.98-105
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• 2022

This study's purpose is to suggest a pedagogical method based on using animated movie in liberal arts English classes and to examine the direction that using animated movie as learning material should take. To this end, in this study, the content understanding and expression concentration stages using animated movie are presented. After students learned in class through animated movie, two tests were conducted to investigate the change in learners' acquisition of English expressions. As a result, subjects' learning of English expressions showed a significant improvement over time. An open-ended questionnaire was also conducted to ascertain learners' satisfaction level and their perceptions of classes using animated movie, with learners' satisfaction found to be high overall (77.1%). Students identified the reasons for their high satisfaction rate as the following: "fun and a touching story", "beneficial composition of textbooks", "efficient teaching methods", "sympathetic topics", and "appropriate difficulty". When using video media in class, instructors should maximize and leverage the advantages of video media, which are rich both in context and in their linguistic aspects.

• Archives of design research
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• v.21
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• pp.233-243
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• 1997

In 1970s, Computer Graphics of still and geometry changed computer Animation of image, and Computer Animation has diversely been used in movie, TV, fashion, sports, education, basic science, medical science, etc. by the development of LSI technology and the large size of computer in 1980s. Since Computer Animation was first used by movie of Futureworld in 1973, we easily experienced the essence of Computer Animation made of the Little Mermaid. Beauty and the Beast, the Lion King, Aladdin, etc. in Disney Animation and Terminator. Jurassic Park, the Mask, etc. in movie. And in other countries that have got the diversely special effect and knowhow in technology are effectively using the Computer Animation now. What situation we Korea are in now, if we compare the Computer Animation with that of other country using the progressive movie\ulcorner Although we first producted the movie title of Ticket, 10years ago, we have rarely been used it in movie, yet. Therefore, we know that it is very important for us to examine the historical and technical side for the purpose of overcoming the technological gap.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.3
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• pp.1422-1427
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• 2013

This paper proposed a movie retrieval system based on sentimental keywords extracted from user's movie reviews. At first, sentimental keyword dictionary is manually constructed by applying morphological analysis to user's movie reviews, and then keyword weights in the dictionary are calculated for each movie with TF-IDF. By using these results, the proposed system classify sentimental categories of movies and rank classified movies. Without reading any movie reviews, users can retrieve movies through queries composed by sentimental keywords.

• The Journal of Information Systems
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• v.16 no.4
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• pp.157-176
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• 2007

Most of the Information Systems(IS) literature has focused on utilitarian or hedonic Information Technology(IT) to explain and predict IT adoption and use. This study investigates the relationships among individuals' beliefs and intention to use of movie website, which has both utilitarian and hedonic characteristics simultaneously. As a theoretical background, this study adopts Technology Acceptance Model(TAM) and Motivation Theory, in which the former is well-known as a theory of IT adoption and use in IS field, and the latter is famous for a theory of individual's behavior in organizational behavior field. With 153 responses, five hypotheses are tested by using structured equation model. The results show that perceived ease of use positively influences perceived usefulness and perceived enjoyment, and that all individuals' beliefs have a positive impact on intention to use of movie web-site. Based upon the study results, movie website's managers and professionals can plan and conduct their courses of action effectively for users' continuous visits on their operating website.

• Annual Conference on Human and Language Technology
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• 2016.10a
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• pp.249-251
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• 2016

다중 화자 대화 시스템에서, 시스템의 입장에서 어느 시점에 참여해야하는지를 아는 것은 중요하다. 이러한 참여 모델을 구축함에 있어서 본 연구에서는 다수의 화자가 대화에 참여하는 영화 대본으로 구축된 MovieDic 말뭉치를 사용하였다. 구축에 필요한 자질로써 의문사, 호칭, 명사, 어휘 등을 사용하였고, 훈련 알고리즘으로는 Maximum Entropy Classifier를 사용하였다. 실험 결과 53.34%의 정확도를 기록하였으며, 맥락 자질의 추가로 정확도 개선을 기대할 수 있다.

• The Research Journal of the Costume Culture
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• v.17 no.4
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• pp.583-599
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• 2009

The purpose of this study is to analyze movie costume of main character and find design characteristic and historical spirit focusing on the movie, in which Ishioka Eiko, Japanese movie costume designer constructing unique design world, participated. The study captured images of three movies such as , and with Digital Multimedia Converting System and analyzed them by focusing on the pictures showing designer's intention and design characteristic well among acquired 319 pictures. The costumes addressing movie costume designer's sense of values are recreated as future-oriented new works and are expressed as creative costumes by acquiring inspiration from past factors, dissolving them and applying up-to-date technology. Movie costume shall reflect historical spirit of our age as movie shows social cultural trend including fashion trend of manufactured age. Ishioka Eiko has searched for the design, which is proper for three principles such as 'be unique', 'be eternal' and 'be innovative' and from the result of analyzing movie costume, it is found that she showed characteristics of symbolism(transmission of the sensitivity), ornamentalism(effective representation as a decorative effect attention) and multiculturalism(harmony of time and culture) as well as uniqueness. The movie costume are different mutually and create new hybrid culture, in which different costume cultures are mixed with current costumes without the restriction to other culture. It is proper for the age of globalization and localization so it is expected that the multiculturalism will be enlarged more.