• International Journal of Computer Science & Network Security
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• 제22권7호
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• pp.352-358
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• 2022

Text mining is an important process used for analyzing the data collected from different sources like videos, audio, social media, and so on. The tools like Natural Language Processing (NLP) are mostly used in real-time applications. In the earlier research, text mining approaches were implemented using long-short memory (LSTM) networks. In this paper, text mining is performed using average-stochastic gradient descent weight-dropped (AWD)-LSTM techniques to obtain better accuracy and performance. The proposed model is effectively demonstrated by considering the internet movie database (IMDB) reviews. To implement the proposed model Python language was used due to easy adaptability and flexibility while dealing with massive data sets/databases. From the results, it is seen that the proposed LSTM plus weight dropped plus embedding model demonstrated an accuracy of 88.36% as compared to the previous models of AWD LSTM as 85.64. This result proved to be far better when compared with the results obtained by just LSTM model (with 85.16%) accuracy. Finally, the loss function proved to decrease from 0.341 to 0.299 using the proposed model

• Journal of information and communication convergence engineering
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• 제20권4호
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• pp.288-294
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• 2022

The media content market has been growing, as various types of content are being mass-produced owing to the recent proliferation of the Internet and digital media. In addition, platforms that provide personalized services for content consumption are emerging and competing with each other to recommend personalized content. Existing platforms use a method in which a user directly inputs video metadata. Consequently, significant amounts of time and cost are consumed in processing large amounts of data. In this study, keyframes and audio spectra based on the YCbCr color model of a movie trailer were extracted for the automatic generation of metadata. The extracted audio spectra and image keyframes were used as learning data for genre recognition in deep learning. Deep learning was implemented to determine genres among the video metadata, and suggestions for utilization were proposed. A system that can automatically generate metadata established through the results of this study will be helpful for studying recommendation systems for media super-personalization.

• 지역과문화
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• 제7권4호
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• pp.69-81
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• 2020

随着互联网公司进军电影产业, 中国的IP电影迅速发展, 并给电影市场带来巨大的商业利益。通过互联网数据, 新媒体等技术, 改变电影制作, 营销和收益模式, 形成新的产业链。本论文试图诊断中国IP电影热潮的现象, 并得出其意义和启示。为此, 选出了不同类型的代表事例来研究存在的问题和相应的改善方案。事例选定了现在IP电影改编中最受瞩目的小说, 漫画, 音乐等3个类型中的代表性作品《悟空传》, 《快把我哥带走》, 《同桌的你》。研究结果显示, 中国的IP电影存在统一化严重, 剧本创作能力不足, 版权等问题。为此, 提出了构建IP版权交易平台, 加强IP创作, 推进IP产业价值链等改善方案。希望通过这项研究进一步完善和推动中国IP电影市场的发展, 打造属于中国IP电影的价值链品牌。

• International journal of advanced smart convergence
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• 제12권4호
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• pp.314-320
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• 2023

This paper examines how the design of female characters in Disney animations is evolving over time, and explores whether these changes are related to the social status of women in modern society. We analyze in detail how Disney's female character design has undergone changes in form, characteristics, and personality with the transition from 2D animation to 3D animation, and show that the change in perception of women in modern society is behind this change. It shows. It deals with changes in the design and personality of female characters, focusing on major Disney animation works before and after 2010. Starting with the movie <Rapunzel>, released in 2010, female characters showed stronger and more active characteristics and changed from traditional Disney princesses. Disney is bringing about this social change by breaking away from the image of an independent woman and showing the growth process of overcoming hardships based on one's abilities and the support of one's family, as well as the increasing number of female characters of various races and appearances. The conclusion was reached that it shows a conscious and active willingness to accept it.

• International Journal of Internet, Broadcasting and Communication
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• 제14권3호
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• pp.115-130
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• 2022

Barrage is an interactive method based on video, and the video itself is visualized from the viewer's point of view to play people's emotions, and it already has an advantage in communication by attracting people's attention using stories and plays. Advances in digital and mobile technology have enabled video viewing anytime, anywhere. Due to the nature of the barrage site that relies on the same video content or playback to participate in video sharing through computers or mobile clients, a barrage that can express users' feelings and thoughts will be added, breaking down the limit of content acceptance by a single user. Barrage satisfy users' entertainment needs, and their influence is growing. Gradually, they are heading to offline movie theaters and TV from barrage videos on the Internet. Attempts to function as offline ammunition facilitated technological innovation for media convergence by converging mobile media with PCs and screens. At the same time, the trend of media convergence shown by coal screens is also a trend of overall technological development. A barrage is an extension of human communication skills. The properties of the barrage fit well with the need for experiential marketing (via video). It can provide a visual experience and create an atmosphere of "surrounding and watching" and eliminate loneliness. Barrage itself provides a function to comment on videos, which is a trigger point for the reason, and donation adds to the amount of information in the video, adding to the fun of the video. Through the barrage, sarcastic, teasing, and expressing emotions can bring entertainment experiences, and users can produce and communicate their shooting text while consuming the satisfaction brought by the shooting. At the same time, Barrage attaches great importance to the needs of the masses, is more individual and diversified, and has commercial significance in line with the current development trend of the Internet. As a new interactive method, barrage contains huge potential value. However, the impact of the interactive way of barrage should also be viewed from a dialectical point of view, how to solve the difficulties in the development of barrage. The way to solve the difficulties in the development of barrage is worth studying. This research will analyze the reasons for the development of barrage and the analysis of Chinese barrage websites, the case analysis of barrage videos, the exploration of the characteristics and values of barrage, and the problems in the process of barrage communication. Provide reference for the development of industrial culture.

• 한국콘텐츠학회논문지
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• 제11권12호
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• pp.28-39
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• 2011

멀티미디어 산업의 발달과 함께 디지털 콘텐츠 시장의 확산을 가져오고 있다. 그 중 인터넷 만화와 같은 디지털 만화 시장의 확장은 급속하게 커지고 있어서, 콘텐츠의 부족과 다양성 때문에 동영상 카투닝에 대한 연구가 계속되고 있다. 지금까지는 동영상 카투닝은 비사실적 렌더링과 말풍선에 초점이 맞추어졌으나, 이러한 것들을 적용하기 위해서는 카투닝 서비스에 적합한 프레임 추출이 우선시 되어야만 한다. 기존의 방법으로는 동영상의 장면전환이 일어나는 샷(shot)안의 프레임을 추출하여, 사용자가 지정한 영역을 임의의 색상으로 렌더링(Rendering)하는 시스템이 있다. 하지만 이러한 방법은 사람의 손을 거치는 반자동적인 방법으로서 정확한 프레임 추출을 위해 사람의 손을 거쳐야하는 단점이 있다. 따라서 본 논문에서는 이러한 문제점을 해결하고, 보다 정확한 카투닝에 적용할 프레임을 추출하기 위해 오디오 및 비디오 분리를 통한 방법을 제안한다. 먼저 동영상으로부터 오디오와 비디오를 분리한다. 오디오는 먼저 MFCC와 영교차율의 특징을 추출하고, 이 특징 정보를 미리 학습된 데이터와 GMM 분류기를 통하여 음악, 음성, 음악+음성으로 분류한 후 음성 영역을 설정한다. 비디오는 히스토그램을 이용한 방법과 같은 일반적인 장면전환 프레임을 추출 후 얼굴 검색을 통해서 만화에서 의미가 있는 프레임을 추출한다. 그 후 음성 영역내에 얼굴이 존재하는 장면전환 프레임이나 일정 시간동안 음성이 지속되는 영역 중 장면전환 프레임을 추출하여 동영상 카투닝에 적합한 프레임을 자동으로 추출한다.

• 한국컴퓨터정보학회논문지
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• 제15권1호
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• pp.149-157
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• 2010

최근에 인터넷 사용이 점차 활발해 짐에 따라, 다른 사람들이 인터넷 상에 올려놓은 의견정보를 참조하고자 하는 수요가 높아지고 있다. 하지만, 이러한인터넷상에존재하는의견들은개개의웹사이트들에만존재하여, 이러한 의견정보들을 사용하고자 할 경우에는 사용자가 일일이 이러한 개개의 모든 웹사이트를 수동으로 찾아보아야 하는 번거로움이 존재하는 문제점이 있다. 본 논문은 웹 콘텐츠에서의 통계기반 웹 마이닝(Web Mining)을 통한 의견 추출 및 분석 시스템에 관한 것으로, 인터넷 상에 존재하는 여러 웹사이트들에 흩어져 있는 웹문서에서 사용자 의견정보들을 자동으로 추출 및 분석한다. 또한, 긍정/부정 의견별로 실시간으로 검색 및 통계를 확인할 수 있는 의견정보 검색 서비스를 간편하게 제공할수 있으며, 의견정보 검색 사용자들은 특정 키워드에 대하여 다른 사용자들의 의견정보를 손쉽게 실시간으로 검색 및 모니터링(Monitoring)할 수 있는 시스템이다. 제안한 기법들은 기존의 다른 기법들과의 비교 실험을 수행하여 실제 성능이 우수함을 증명하였다. 성능 평가는 긍정/부정 의견정보를 추출하는 기능의 성능 평가를 실시하였다. 그 적용 사례로 대표적인 영화 리뷰 문장 실험 데이터를 대상으로 실험하고 그 결과를 분석하였다.

• Asia pacific journal of information systems
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• 제17권4호
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• pp.187-206
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• 2007

The development of computer and information technology has been combined with the information superhighway internet infrastructure, so information widely spreads not only in special fields but also in the daily lives of people. Information ubiquity influences the traditional way of transaction, and leads a new E-commerce which distinguishes from the existing E-commerce. Not only goods as physical but also service as non-physical come into E-commerce. As the scale of E-Commerce is being enlarged as well. It keeps people from finding information they want. Recommender systems are now becoming the main tools for E-Commerce to mitigate the information overload. Recommender systems can be defined as systems for suggesting some Items(goods or service) considering customers' interests or tastes. They are being used by E-commerce web sites to suggest products to their customers who want to find something for them and to provide them with information to help them decide which to purchase. There are several approaches of recommending goods to customer in recommender system but in this study, the main subject is focused on collaborative filtering technique. This study presents a possibility of pre-evaluation for the prediction performance of customer's preference in collaborative filtering before the process of customer's preference prediction. Pre-evaluation for the prediction performance of each customer having low performance is classified by using the statistical features of ratings rated by each customer is conducted before the prediction process. In this study, MovieLens 100K dataset is used to analyze the accuracy of classification. The classification criteria are set by using the training sets divided 80% from the 100K dataset. In the process of classification, the customers are divided into two groups, classified group and non classified group. To compare the prediction performance of classified group and non classified group, the prediction process runs the 20% test set through the Neighborhood Based Collaborative Filtering Algorithm and Correspondence Mean Algorithm. The prediction errors from those prediction algorithm are allocated to each customer and compared with each user's error. Research hypothesis : Two research hypotheses are formulated in this study to test the accuracy of the classification criterion as follows. Hypothesis 1: The estimation accuracy of groups classified according to the standard deviation of each user's ratings has significant difference. To test the Hypothesis 1, the standard deviation is calculated for each user in training set which is divided 80% from MovieLens 100K dataset. Four groups are classified according to the quartile of the each user's standard deviations. It is compared to test the estimation errors of each group which results from test set are significantly different. Hypothesis 2: The estimation accuracy of groups that are classified according to the distribution of each user's ratings have significant differences. To test the Hypothesis 2, the distributions of each user's ratings are compared with the distribution of ratings of all customers in training set which is divided 80% from MovieLens 100K dataset. It assumes that the customers whose ratings' distribution are different from that of all customers would have low performance, so six types of different distributions are set to be compared. The test groups are classified into fit group or non-fit group according to the each type of different distribution assumed. The degrees in accordance with each type of distribution and each customer's distributions are tested by the test of ${\chi}^2$ goodness-of-fit and classified two groups for testing the difference of the mean of errors. Also, the degree of goodness-of-fit with the distribution of each user's ratings and the average distribution of the ratings in the training set are closely related to the prediction errors from those prediction algorithms. Through this study, the customers who have lower performance of prediction than the rest in the system are classified by those two criteria, which are set by statistical features of customers ratings in the training set, before the prediction process.

• 한국전자통신학회논문지
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• 제10권4호
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• pp.477-482
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• 2015

본 논문에서는 사물인터넷 사용자가 유니티 기반의 스마트 미디어에서 3차원 형태로 표출하고자 유니티 런처 플랫폼을 제안하였다. 안드로이드 기반의 홈 게이트웨이는 유니티 엔진을 연동하는 플랫폼에서 동영상과 3차원 무비 텍스쳐가 동시에 연동하게 되었다. 유니티 런처 기반의 플랫폼은 3차원 공간에서 IoT 센서의 위치를 표출하는 유니티 활용 방안을 설계하였다. 제안한 스마트 게이트웨이 플랫폼에서 3차원 사물인터넷 센서의 위치를 추적하는 방식은 센서의 무선신호세기인 RSSI 신호와 방위각 정보를 활용함으로서 3차원 공간 상에서 IoT 센서의 3D 위치를 표출할 수 있다. 유니티 런쳐가 탑재된 스마트 게이트웨이 플랫폼은 3차원 입체모형으로 IoT 센서의 위치를 표출하기 위해 2D 평면도를 3차원으로 변환할 수 있다. 이러한 플랫폼은 3차원 큐브 형태로 센서의 위치 표시함으로서 IoT 센서의 동작 상태를 모니터링 할 수 있으며, 설치에서 폐기까지의 생애 주기를 표시할 수 있다.

• 한국의상디자인학회지
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• 제9권2호
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• pp.179-192
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• 2007

This study is to search for a new area and a new kind of occupation for fashion in the field of multi-media such as a movie, drama, mass-culture and advertisement, as a basic investigation to improve a potential of a development of fashion in the future, to keep in step with the trend of the changes under the environment of cultural renovation. In this reports, the field and vision of new contents in fashion will be proposed. The definition and environment of multi-media were examined, and various kinds and work areas of new fashion specialists were defined. 12 professionals in each fields relative to multi-media were selected and the status of affairs, problems and requirements of fashion specialists were investigated through the in-depth interviews with them. Finally new fields and visions were suggested on it's future course. The kind of fashion-specialist on the field related to multi-media were like this: 1. Fashion-stylist, Art-director and Image-maker for star on the field of Video industry. 2. Fashion-illustrator for making animation-game character, Avatar fashion product designer and Internet shopping buyer for Online-business industry. 3. Fashion PR director, Fashion-photo stylist for Advertisement industry. 1 classified new field on the field related to multi-media as the above, and I researched the role of specialist in each field and the status of affairs and vision.