• Proceedings of the Korean Institute of Industrial Safety Conference
• /
• 2005.04a
• /
• pp.7-12
• /
• 2005

• Proceedings of the Korea Air Pollution Research Association Conference
• /
• 2007.10a
• /
• pp.376-377
• /
• 2007

• Proceedings of the Korea Contents Association Conference
• /
• 2015.05a
• /
• pp.27-28
• /
• 2015

내러티브의 복잡도는 수용자의 이해와 흥미에 직접적으로 영향을 미치기 때문에 창작과정에서 체계적으로 관리되어야 한다. 본 논문에서는 내러티브 구성에 있어서의 지식 분배 작업에 초점을 맞추어 정보 엔트로피 개념을 활용한 복잡도 평가 방법을 개발하였다. 수용자의 지식상태 변화 과정에서 발생하는 정보량을 엔트로피로 계산하여 복잡도 척도로 활용하였다. 실제 영화 내러티브를 대상으로 사례 연구를 수행하였고, 본 방법이 내러티브의 구조적 특성과 전개과정에서의 변화를 효과적으로 반영함을 확인하였다.

• Proceedings of the Korea Air Pollution Research Association Conference
• /
• 2003.11a
• /
• pp.353-355
• /
• 2003

시화공단에서 악취물질의 원인규명을 위한 공동연구가 실시된바 있다. 이 연구에서 본 연구팀은 주요 악취유발물질인 질소화합물과 카르보닐화합물의 실시간 모니터링 기술을 소개한 바 있다. 이 연구의 후속사업으로 금년 6월부터 3개월에 걸친 장기모니터링을 실시하여 이 기술의 현장 적용성과 악취모니터링의 유용성을 평가한바 있다. 이번 연구에서는 질소화합물, 카르보닐화합물, 유황화합물에 대한 세 분석시스템을 평가하였다. (중략)

• Journal of Digital Convergence
• /
• v.12 no.8
• /
• pp.329-335
• /
• 2014

Collaborative filtering has been popular in commercial recommender systems, as it successfully implements social behavior of customers by suggesting items that might fit to the interests of a user. So far, most common method to find proper items for recommendation is by searching for similar users and consulting their ratings. This paper suggests a new similarity measure for movie recommendation that is based on genre interest, instead of differences between ratings made by two users as in previous similarity measures. From extensive experiments, the proposed measure is proved to perform significantly better than classic similarity measures in terms of both prediction and recommendation qualities.

• Journal of the Korea Society of Computer and Information
• /
• v.19 no.9
• /
• pp.93-101
• /
• 2014

Movie stories can be retrieved efficiently by analyzing a script, which is a blueprint of the movie. Although the movie script is described in the formatted structure of Final Draft, it is hard to restore the type without analyzing the story of the sentences since the scripts open on the website are mostly broken. For this purpose, it is necessary to develop and provide the web-based script analysis software so that users collaboratively and freely check and correct the errors in the results after automatically parsing the script. Hence, in this paper we suggest the structure of the web-based collaborative script analysis platform that enables users to modify and filter the type error of the script for high level of film data accumulation and performance evaluation for the implementation results is conducted. Through the experiment, accuracy of automatically parsing appears to be 64.95% and performance of modification by collaboration showed 99.58% of accuracy of parsing with errors mostly corrected after passing through 5 steps of modification.

• KIPS Transactions on Computer and Communication Systems
• /
• v.4 no.9
• /
• pp.289-296
• /
• 2015

The explosive growth of information has been difficult for users to get an appropriate information in time. The various ways of new services to solve problems has been provided. As customized service is being magnified, the personalized recommendation system has been important issue. Collaborative filtering system in the recommendation system is widely used, and it is the most successful process in the recommendation system. As the recommendation is based on customers' profile, there can be sparsity and cold-start problems. In this paper, we propose personalized movie recommendation system using collaborative filtering techniques and context-based techniques. The context-based technique is the recommendation method that considers user's environment in term of time, emotion and location, and it can reflect user's preferences depending on the various environments. In order to utilize the context-based technique, this paper uses the human emotion, and uses movie reviews which are effective way to identify subjective individual information. In this paper, this proposed method shows outperforming existing collaborative filtering methods.

• Journal of Digital Convergence
• /
• v.14 no.8
• /
• pp.453-460
• /
• 2016

This study aimed to compare the systems of ticketing application programs of three major movie theaters, CGV, Megabox, Lotte Cinema, with each other and evaluate the usability, and find problems to figure out user experiences for more convenient mobile ticketing. Experimental subjects with experiences of using apps of the movie theaters were recruited; First, as a primary task, they reserved movie tickets with each of the movie theater apps; Second, they had in-depth interviews with questions based on the model of Creating Pleasurable Interfaces by Stephen Anderson. As a result, users preferred the composition with information in order in overall, in which ticketing process went smoothly. In particular, users were more satisfied with convenient payment applications. Therefore, as an improving way, it is required to design an interface for users to recognize at a glance and a payment system within an app, not to design separate payment system out of the app. I hope this study will help actively conduct researches to maximize the usability in a way to reserve movie tickets through smartphone apps.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.21 no.3
• /
• pp.67-72
• /
• 2021

Association rule mining is a method of showing the relationship between patterns hidden in several tables. These days, granulation logic is used to add more detailed meaning to association rule mining. In addition, unlike the existing system that recommends using existing data, the granulation related rules can also recommend new subscribers or new products. Therefore, determining the qualitative size of the granulation of the association rule determines the performance of the recommendation system. In this paper, we propose a granulation method for subscribers and movie data using fuzzy logic and Shannon entropy concepts in order to understand the relationship to the movie evaluated by the viewers. The research is composed of two stages: 1) Identifying the size of granulation of data, which plays a decisive role in the implications of the association rules between viewers and movies; 2) Mining the association rules between viewers and movies using these granulations. We preprocessed Netflix's MovieLens data. The results of meanings of association rules and accuracy of recommendation are suggested with managerial implications in conclusion section.

• Asia Marketing Journal
• /
• v.12 no.2
• /
• pp.1-25
• /
• 2010

Motion pictures are so typical experience goods that consumers tend to look for more credible information. Hence, movie audiences consider movie viewers' reviews more important than the information provided by the film distributor. Recently many portal sites allow consumers to post their reviews and opinions so that other people check the number of consumer reviews and scores before going to the theater. There are a few previous researches studying the electronic word of mouth(eWOM) effect in the movie industry. They found that the volume of eWOM influenced the revenue of the movie significantly but the valence of eWOM did not affect it much (Liu 2006). The goal of our research is also to investigate the eWOM effects in general. But our research is different from the previous studies in several aspects. First, we study the eWOM effect in Korean movie industry. In other words, we would like to check whether we can generalize the results of the previous research across countries. The similar econometric models are applied to Korean movie data that include 746,282 consumer reviews on 439 movies. Our results show that both the valence(RATING) and the volume(LNMSG) of the eWOM influence weekly movie revenues. This result is different from the previous research findings that the volume only influences the revenue. We conjectured that the difference of self construal between Asian and American culture may explain this difference (Kitayama 1991). Asians including Koreans have more interdependent self construal than American, so that they are easily affected by other people's thought and suggestion. Hence, the valence of the eWOM affects Koreans' choice of the movie. Second, we find the critical defect of the previous eWOM models and, hence, attempt to correct it. The previous eWOM model assumes that the volume of eWOM (LNMSG) is an independent variable affecting the movie revenue (LNREV). However, the revenue can influence the volume of the eWOM. We think that treating the volume of eWOM as an independent variable a priori is too restrictive. In order to remedy this problem, we employed a simultaneous equation in which the movie revenue and the volume of the eWOM can affect each other. That is, our eWOM model assumes that the revenue (LNREV) and the volume of eWOM (LNMSG) have endogenous relationship where they influence each other. The results from this simultaneous equation model showed that the movie revenue and the eWOM volume interact each other. The movie revenue influences the eWOM volume for the entire 8 weeks. The reverse effect is more complex. Both the volume and the valence of eWOM affect the revenue in the first week, but only the volume affect the revenue for the rest of the weeks. In the first week, consumers may be curious about the movie and look for various kinds of information they can trust, so that they use the both the quantity and quality of consumer reviews. But from the second week, the quality of the eWOM only affects the movie revenue, implying that the review ratings are more important than the number of reviews. Third, our results show that the ratings by professional critics (CRATING) had negative effect to the weekly movie revenue (LNREV). Professional critics often give low ratings to the blockbuster movies that do not have much cinematic quality. Experienced audiences who watch the movie for fun do not trust the professionals' ratings and, hence, tend to go for the low-rated movies by them. In summary, applied to the Korean movie ratings data and employing a simultaneous model, our results are different from the previous eWOM studies: 1) Koreans (or Asians) care about the others' evaluation quality more than quantity, 2) The volume of eWOM is not the cause but the result of the revenue, 3) Professional reviews can give the negative effect to the movie revenue.