• Proceedings of the Korean Society of Computer Information Conference
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• 2020.01a
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• pp.15-18
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• 2020

특정 영화의 스크린 독과점이 꾸준히 논란이 되고 있다. 본 논문에서는 영화 스크린 분배의 불평등성을 지적하고 이에 대한 개선을 요구할 근거로 머신러닝 기법을 활용한 영화 관람객 예측 모델을 제안한다. 이에 따라 KOBIS, 네이버 영화, 트위터, 구글 트렌드에서 수집한 3,143개의 영화 데이터를 이용하여 랜덤포레스트와 그라디언트 부스팅 기법을 활용한 영화 관람객 예측 모델을 구현하였다. 모델 평가 결과, 그라디언트 부스팅 모델의 RMSE는 600,486, 랜덤포레스트 모델의 RMSE는 518,989로 랜덤포레스트 모델의 예측력이 더 높았다. 예측력이 높았던 랜덤포레스트 모델을 활용, 상영관을 크게 확보하지 못 했던 봉준호 감독의 영화 '옥자'의 상영관 수를 조절하여 관람객 수를 예측, 6,345,011명이라는 결과를 제시한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.766-768
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• 2023

본 논문에서는 전시회의 관람객을 탐지하고 추적하여 실시간으로 속도를 측정하여 전시 부스에서 관람객의 속도가 줄어드는 것을 파악한 후 멈춤 행동을 판단하는 시스템을 제안한다. 해당 시스템은 전시회 부스에 웹 캠을 설치하여 그 관찰 영역에 들어온 관람객을 인식한 후 관람객의 속도를 예측하고 관람객의 속도 변화를 논문에서 정의한 관람객의 여러 상태로 변화시킨 후 새롭게 정의한 멈춤 행동에 해당하는 관람객의 관심도를 추정하게 된다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.765-767
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• 2023

본 논문에서는 웹캠을 이용하여 전시관의 관람객을 추적하고, 그 관람객들의 속도를 추정하여 전시품 앞에서 속도가 줄어드는 것을 이용하여 관심도의 레벨을 추정하는 시스템을 제안한다. 제안 시스템은 관심 관람객의 특성을 분석하기 위하여, 일정 크기의 전시 부스에 설치하는 것을 가정하였다. 제안 시스템은 관찰영역에 진입하는 관객을 인식하고, 관객의 움직이는 속도를 예측하며, 관객의 속도가 관찰 영역내에서 줄어들면서 멈춤 동작을 하는 것을 인식하여 관람객의 관심레벨을 조정하도록 하였다. 뎁스 카메라를 이용하지 않고 저가의 웹캠을 이용하므로 전시관에 쉽게 설치하여 적용할 수 있을 것으로 기대한다.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.67-83
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• 2018

The Korean film industry with significant increase every year exceeded the number of cumulative audiences of 200 million people in 2013 finally. However, starting from 2015 the Korean film industry entered a period of low growth and experienced a negative growth after all in 2016. To overcome such difficulty, stakeholders like production company, distribution company, multiplex have attempted to maximize the market returns using strategies of predicting change of market and of responding to such market change immediately. Since a film is classified as one of experiential products, it is not easy to predict a box office record and the initial number of audiences before the film is released. And also, the number of audiences fluctuates with a variety of factors after the film is released. So, the production company and distribution company try to be guaranteed the number of screens at the opining time of a newly released by multiplex chains. However, the multiplex chains tend to open the screening schedule during only a week and then determine the number of screening of the forthcoming week based on the box office record and the evaluation of audiences. Many previous researches have conducted to deal with the prediction of box office records of films. In the early stage, the researches attempted to identify factors affecting the box office record. And nowadays, many studies have tried to apply various analytic techniques to the factors identified previously in order to improve the accuracy of prediction and to explain the effect of each factor instead of identifying new factors affecting the box office record. However, most of previous researches have limitations in that they used the total number of audiences from the opening to the end as a target variable, and this makes it difficult to predict and respond to the demand of market which changes dynamically. Therefore, the purpose of this study is to predict the weekly number of audiences of a newly released film so that the stakeholder can flexibly and elastically respond to the change of the number of audiences in the film. To that end, we considered the factors used in the previous studies affecting box office and developed new factors not used in previous studies such as the order of opening of movies, dynamics of sales. Along with the comprehensive factors, we used the machine learning method such as Random Forest, Multi Layer Perception, Support Vector Machine, and Naive Bays, to predict the number of cumulative visitors from the first week after a film release to the third week. At the point of the first and the second week, we predicted the cumulative number of visitors of the forthcoming week for a released film. And at the point of the third week, we predict the total number of visitors of the film. In addition, we predicted the total number of cumulative visitors also at the point of the both first week and second week using the same factors. As a result, we found the accuracy of predicting the number of visitors at the forthcoming week was higher than that of predicting the total number of them in all of three weeks, and also the accuracy of the Random Forest was the highest among the machine learning methods we used. This study has implications in that this study 1) considered various factors comprehensively which affect the box office record and merely addressed by other previous researches such as the weekly rating of audiences after release, the weekly rank of the film after release, and the weekly sales share after release, and 2) tried to predict and respond to the demand of market which changes dynamically by suggesting models which predicts the weekly number of audiences of newly released films so that the stakeholders can flexibly and elastically respond to the change of the number of audiences in the film.

• Journal of Digital Contents Society
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• v.19 no.1
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• pp.27-33
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• 2018

In this study, we analyze the big data of visitors who are looking for a sports stadium in marketing field and conduct research to provide customized marketing service to consumers. For this purpose, we intend to derive a similar visitor group by using the K-means clustering method. Also, we will use the K-nearest neighbors method to predict the store of interest for new visitors. As a result of the experiment, it was possible to provide a marketing service suitable for each group attribute by deriving a group of similar visitors through the above two algorithms, and it was possible to recommend products and events for new visitors.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.01a
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• pp.241-242
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• 2018

야구 관람객들은 주로 자기가 선호하는 팀의 경기나 이길 가능성이 높은 경기를 관람하고자 한다. 때문에 시중에 지난 경기, 당일의 경기, 미래 경기에 대한 정보를 얻을 수 있는 KBO 사이트와 경기 승/패를 예측하기 위한 정보를 얻을 수 있는 사이트에서 경기 기록에 대한 정보를 얻어 관람 일을 결정하는데 도움을 얻는다. 따라서 본 연구에서는 데이터마이닝을 통하여 프로야구 팬들이 특정 팀의 승/패를 예측하는데 사용할 수 있는 유용한 규칙과 패턴을 도출해보고자 한다.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1999.05a
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• pp.118-134
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• 1999

가상 현실 미술관에서 시각적 요소인 해상도는 참여자에게 매우 중요한 인공현실감을 제공하며 실제 세계와의 상호 교류의 차이의 극복 요소로서 매우 중요한 부분으로 볼 수 있다. 이러한 시각적 측면을 중심으로 가상현실 전시관에서 관람객과 전시물 사이의 거리에 따른 감상 위치를 분석하고, avatar의 이동에 따른 원근법을 적용하여 해상도를 동적으로 변화시킨다. 특히, 가상 공간의 이동 예측 및 거리 측정에 따른 해상도의 변화는 현장감 향상에 도움을 준다.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.05a
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• pp.316-318
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• 2021

영화 수익에 있어 영화의 흥행 여부는 중요한 영향을 끼친다. 영화 흥행 요인은 영화 산업의 규모가 커지면서 많은 제작사들 및 투자자들이 고려해야 하는 사항이 되었다. 따라서 영화의 흥행을 예측하기 위한 많은 모델이 연구되었다. 본 연구의 목적은 선행연구에서 흥행에 유의미한 영향을 끼친다고 밝혀진 스크린 수, 감독명, 제작사명 등의 내재적인 속성과 더불어 온라인 구전 변수를 사용하여 영화 흥행 예측 모델을 만드는 것이다. 이때 기사 수, 블로그 수와 같이 온라인 구전의 크기를 나타내는 변수들을 사용하는 대신 개봉 후 첫 주간의 관람객 리뷰를 텍스트마이닝을 이용하여 전체 리뷰 중 긍정 리뷰의 비율에 따라 점수를 매긴 후 독립변수로 사용한다. 그 후, 데이터 마이닝 기법을 활용하여 만든 모델에 앞서 언급한 독립변수를 입력 값으로 사용하여 영화의 흥행을 예측한다. 최종적으로 의사결정트리와 로지스틱회귀를 수행한 결과 영화 흥행에 영향을 주는 독립변수를 찾고 모델의 성능을 평가하였다. 로지스틱회귀의 결과 관객 수, 평점이 영화의 흥행에 특히 유의한 영향을 끼치는 변수로 선정되었고 리뷰 역시 유의한 변수로 선정되었다. 이때 만들어진 모델은 약 90%의 높은 수준의 정확도를 보여주었다. 의사결정트리의 결과 관객 수가 가장 중요한 변수로 선정되었다.

• Korean Security Journal
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• no.30
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• pp.7-32
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• 2012

Korea faces The 2014 Incheon Asian Games and 2018 Pyungchang Winter Olympics. It is imperative to hold a safe event for the economic benefits, enhancing Korea's image, social integration, national harmony and unity in order to be evaluated as a successful international event. Furthermore, since the international event tends to draw many spectators, the host country must be ready to accommodate a large number of injured people in the event of an accident or terror attack. As stadiums for international events are where a large number of spectators gather in, a large refuge is essential, when dangerous situations happen. In this study, evacuation simulation was conducted using three scenarios in order to predict escape behaviors of spectators during the large escape by destruction of safety systems of stadiums and assess escape safety. As the result, the following results and proposals were extracted. Firstly, it is considered that dangerous situations during the security of stadiums should be predicted in advance and concrete plans for a large refuge of spectators have to be established to minimize damage. Secondly, it was found that the reduction in evacuation exits has an important impact on evacuation in an emergency situation. It implies that securing escape exits are quite important. Thirdly, there were areas where spectators stayed, due to blocked escape exits, while they were dispersed and concentrated at once. It demonstrates that security plans considering properties of facilities are required to solve these problems.

• Journal of Korea Entertainment Industry Association
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• v.13 no.2
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• pp.79-91
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• 2019

In the entertainment industry, risk management is crucial for securing competitiveness due to the risk of investment. The competitiveness of contents is reinforced when external factors such as industrial environment and internal factors centering on involving mechanism are simultaneously provided. The involving mechanism is a form of cognitive response behavior of the audience and occurs through signal processing of the brain when watching the image contents. The signal processing of the brain related to the contents watching is mainly performed in the working memory area, and in the case of the captivating movie, the information other than the contents transmitted to the audience is blocked to generate a temporary dissociation state. A dissociation state similar to a symptom such as hypnosis or amnesia occurs when the audience's level of involving is high. On the other hand, contents information in which the audience is concentrating his attention is used intensively for constructing future thinking through an episodic buffer while the inflow of external information is relatively blocked or delayed. The spectator's future thinking configuration takes the form of a hypothesis-forming activity and is based on the predictability of the brain. When these hypothesized behaviors correspond to the problem solving simulation of story and predictability which is an evolutionary function of the brain, the audience' s brain is involved in the contents at a high level. In order for the act to be effective, the factors such as the background of the hypothesis, the subject of the hypothesis, the internal information of the person, the type and position and quantity of the hypothesis information, and the hypothesis relevance and type of information are important. Based on these factors, analysis of the Kim Eun Sook Drama 'Goblin' shows that the above elements are operated in a very organic and meaningful way.