• Information Systems Review
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• v.16 no.3
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• pp.113-134
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• 2014

Since a movie is an experience goods, purchase can be decided upon preliminary information and evaluation. There are ongoing researches on what impact online reviews might have on movie revenues. Whereas research in the past was focused on the effect of online reviews. The influence of online reviews appears to be significant in products like a movie because it is difficult to evaluate the feature prior to "consuming" the product. Since an online review is regarded to be objective, consumers find it more trustworthy. Contrary to prior research focused on movie review ratings and volume, we focus moves on movie features related specific reviews. This research proposes a predictive model for movie revenue generation. We decided 15 criteria to classify movie features collected from online reviews through the online review mining and made up feature keyword list each criterion. In addition, we performed data preprocessing and dimensional reduction for data mining through factor analysis. We suggest the movie revenue predictive model is tested using discriminant analysis. Following the discriminant analysis, we found that online review factors can be used to predict movie popularity and revenue stream. We also expect using this predictive model, marketers and strategic decision makers can allocate their resources in more parsimonious fashion.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.1
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• pp.43-50
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• 2009

This paper caters the need of acquiring the principal objects, characters, and scenes from a video in order to entertain the image based query. The movie frames are divided into frames with 2D representative images called "key frames". Various regions in a key frame are marked as key objects according to their textures and shapes. These key objects serve as a catalogue of regions to be searched and matched from rest of the movie, using viewpoint invariant regions calculation, providing the location, size, and orientation of all the objects occurring in the movie in the form of a set of structures collaborating as video profile. The profile provides information about occurrences of every single key object from every frame of the movie it exists in. This information can further ease streaming of objects over various network-based viewing qualities. Hence, the method provides an effective reduced profiling approach of automatic logging and viewing information through query by example (QBE) procedure, and deals with video streaming issues at the same time.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.430-441
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• 2022

With the development of ICT technology, various mobile applications have appeared one after another, and they have penetrated deeply into the lives of individuals. In order to explore the key factors that movie content-related applications should have through empirical studies, this study used the information system success model to investigate the influence of each quality factor on movie consumers' attitudes toward movies and their viewing intentions. As a result of the study, it was derived that the most important factor among the quality factors of movie content-related applications was the information quality factor, followed by the service quality being the next most important factor. In this study, based on the results of this study, the direction of application related to movie contents as a new distribution channel was proposed by suggesting a way to improve applications related to movie contents for the development of the domestic movie industry.

• Journal of Information Processing Systems
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• v.9 no.1
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• pp.157-172
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• 2013

There are many recommendation systems available to provide users with personalized services. Among them, the most frequently used in electronic commerce is 'collaborative filtering', which is a technique that provides a process of filtering customer information for the preparation of profiles and making recommendations of products that are expected to be preferred by other users, based on such information profiles. Collaborative filtering systems, however, have in their nature both technical issues such as sparsity, scalability, and transparency, as well as security issues in the collection of the information that becomes the basis for preparation of the profiles. In this paper, we suggest a movie recommendation system, based on the selection of optimal personal propensity variables and the utilization of a secure collaborating filtering system, in order to provide a solution to such sparsity and scalability issues. At the same time, we adopt 'push attack' principles to deal with the security vulnerability of collaborative filtering systems. Furthermore, we assess the system's applicability by using the open database MovieLens, and present a personal propensity framework for improvement in the performance of recommender systems. We successfully come up with a movie recommendation system through the selection of optimal personalization factors and the embodiment of a safe collaborative filtering system.

• 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 the Korea Society of Computer and Information
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• v.22 no.7
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• pp.125-131
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• 2017

It is not easy for the user to find the information that is appropriate for the user among the suddenly increasing information in recent years. One of the ways to help individuals make decisions in such a lot of information is the recommendation system. Although there are many recommendation methods for such recommendation systems, a representative method is collaborative filtering. In this paper, we design and implement the movie recommendation system on user-based collaborative filtering of apache mahout. In addition, Pearson correlation coefficient is used as a method of measuring the similarity between users. We evaluate Precision and Recall using the MovieLens 100k dataset for performance evaluation.

• Journal of Korea Society of Digital Industry and Information Management
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• v.14 no.2
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• pp.61-67
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• 2018

This media conversion in which webtoons are remediated to movies and dramas has taken off since the mid-2000s. Webtoons may be favorable for media conversion into movies and dramas as the story as finished and has proven to be fun with a fixed readership: however, only a small number of webtoon were successful box office hits or received high viewer ratings. Then in 2017, the movie based on the webtoon, succeed in attracting more more then 10 million viewers. In this regard, this study derived the success factors by comparing and analyzing the narrative structure and visual elements of , which was the biggest hit movie, with the original webtoon. The case analysis showed that there are two necessary elements for success: a text configuration of strategy optimized for media conversion, which is based on understanding the different media characteristics of webtoon and movie; and a configuration strategy that exaggerates the personalities of the characters and compresses the story of a webtoon which features various events and many characters in a long series, in consideration of the characteristics of movie which needs to give a big impact in 2 hours.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10c
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• pp.239-242
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• 2007

본 논문에서는 다수의 저가형 웹캠(Web Cam)으로 촬영된 다각도의 다중 영상을 입력으로 받아 이들을 자연스럽게 연결하여 임의의 각도에서 물체의 모습을 관찰할 수 있도록 하는 ${\ulcorner}$다중 카메라 촬영 영상을 이용한 Object Movie 생성 기반 기술${\lrcorner}$을 제안한다. 기존 Object Movie 생성도구들이 다중의 이미지들을 스티칭(stiching)하기 위해 정확한 카메라의 위치와 방향을 요구하는 데 비해, 제안된 방법은 고가의 트랙장비를 사용하기 어려운 경우에 다수의 저가형 웹캠으로 촬영된 카메라의 위치와 방향을 보정하는 단계를 추가하여 트랙장비를 사용한 것과 같은 매끄러운 영상을 생성할 수 있도록 하였다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.197-200
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• 2018

The aim of current research is to suggest a interface for movie reviews at a glance through semantic network analysis. The implication of this study is to systematically investigate the structure of eWoM. Specifically, by visualizing semantic networks of movie reviews this study attempts to provide a prototype of a possible review system that can check the response of movie viewer at a glance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.124-125
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• 2018

The purpose of this study was to explore the sensibilities of audiences about the buildings and backgrounds in the movie with Harry Potter, a magic movie. For this purpose, the sensibility vocabulary suitable for the background of the movie was derived. I expect that the building background of the movie will have an sensibility impact on the audience and I hope that it will help to understand the Western classical Gothic style and culture in an emotional aspect.