• Journal of Digital Contents Society
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• v.18 no.6
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• pp.1119-1125
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• 2017

Genres and actions of stories can be used to classify stories, and used effectively as well for visualizing story properties. This paper proposes a Genre-Action coordinate system for visualizing story property data in 2-dimension that has similarities between the genre and action items along the axes, i.e. a property of spatial continuum. With the proposed Genre-Action coordinate system we found that the genre and action items in the axes are arranged according to their similarities and we were able to achieve a spatially meaningful visualization of story properties where the related data form clusters.

• The Journal of the Korea Contents Association
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• v.16 no.10
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• pp.645-655
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• 2016

The purpose of this study is to search shot clip' using variables influencing on the VOD purchase intention and watching intention of real-time broadcasting. This research focused on usage motivation, usage experience such as use time, time of utilization, genre, utilization pattern. Controlling demographic factors, results show that personal relation, benefit against whole broadcast, education genre, watching video, video sharing and recommendation were statistically influential to VOD purchase intention. And, results show that flexibility of use, drama/movie genre, read and write comments were statistically influential to watching intention of real-time broadcasting.

• Journal of Korea Game Society
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• v.10 no.3
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• pp.61-71
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• 2010

This study looks into the usage pattern in online games based on genres and socio-demographic characteristics. Compared to the prior studies that adopted survey as their main research method, this study has analyzed the actual data of game login records and adopted parametric modeling and mathematical approach. In terms of the socio-demographic characteristics, the following facts were confirmed: men > women by gender, students > white-collars > housewives > blue-collars > self-employed > jobless(etc.) by occupation, college graduates > K-12 students > high-school graduates > undergrads & grads by academic background, 3∼5 million > 1∼3 million > over 5 million > less than 1 million by income levels, and not married > married by marital status. In terms of genres, the population of the players is in the order of web board games, RPG, action/racing/shooting, and sports. The RPG game is confirmed to have a higher level of MCR (Max Concurrent User Ratio) than any other genres. On the other hand, the hypothesis on the difference in Repeated Use Ratio according to genres is rejected. This study has also confirmed that interactions exist between gender and age; genre and gender; genre and age among online game users, and conducted post-hoc analysis about those interactions.

• Journal of Korea Multimedia Society
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• v.10 no.7
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• pp.817-826
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• 2007

The existing a music genre classification research used signal feature of the part which gets 20 seconds interval of the random or the $40%{\sim}45%$ after in the music. This paper propose it to increase the accuracy of existing research to classify music genre using climax part in the music. Generally the music is divided to three parts; introduction, progress and climax. And the climax is the part which the music emphasizes and expresses the feature of the music best. So, we can get efficient result if the climax is used, when the music classify. We can get the climax in the music finding the tempo and node which uses FFT and the maximum waveform from each node. In this paper, we did a genre classification experiment which uses existing research method and proposing method. The existing method expressed 47% accuracy. And proposing method expressed 56% accuracy which is improved than existing method.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.06a
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• pp.90-91
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• 2016

본 논문에서는 스펙트로그램을 이용한 딥 러닝 기반의 오디오 장르 분류 기술을 제안한다. 기존의 오디오 장르 분류는 대부분 GMM 알고리즘을 이용하고, GMM의 특성에 따라 입력 성분들이 서로 직교한 성질을 갖는 MFCC를 오디오의 특성으로 사용한다. 그러나 딥 러닝을 입력의 성질에 제한이 없으므로 MFCC보다 가공되지 않은 특성을 사용할 수 있고, 이는 오디오의 특성을 더 명확히 표현하기 때문에 효과적인 학습을 할 수 있다. 본 논문에서는 딥 러닝에 효과적인 특성을 구하기 위하여 스펙트로그램(spectrogram)을 사용하여 오디오 특성을 추출하는 방법을 제안한다. 제안한 방법을 사용한면 MFCC를 특성으로 하는 딥 러닝보다 더 높은 인식률을 얻을 수 있다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2017.06a
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• pp.29-30
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• 2017

본 논문에서는 인간의 청각 기관을 모델링 한 스파이크그램 (spikegram)을 이용한 심층 신경망 기반의 음악 장르 분류 기술을 제안한다. 분류 대상은 GTZAN 데이터 세트의 10개 장르로 정의한다. 본 논문에서는 청각 기관의 인식 방법을 모델링한 방법을 이용하여 스파이크그램을 구하고, 스파이크그램에서 새로운 특성 벡터를 추출하는 방법을 제안한다. 제안하는 방법을 통해 심층 신경망에 적합한 특성 벡터를 구하고 이렇게 구한 특성 벡터로 신경망을 학습시켜 기존에 사용하던 다양한 방법들보다 높은 성능을 얻을 수 있다.

• Korean journal of communication and information
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• v.57
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• pp.181-201
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• 2012

Classic cultivation theory and research has been noted for its failure to capture subtle variation in effects by genre and to consider tangible and practical dependent variables. Redressing these limitations, this study aimed at extending cultivation theory frame to incorporating fatalistic attitudes and reality television viewing, especially with the mediator of perceived realism. We first replicated the original cultivation effect by showing the significant effect of overall TV viewing. Even controlling for overall TV viewing, reality-based program use showed positive association with fatalistic beliefs; furthermore, the effect remained significant, additionally controlling for news(fact) use and drama(fiction) use. In a nutshell, the cultivation effect of reality-based TV program on fatalistic beliefs turns out quite stable even after controlling other competing genres.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.1
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• pp.27-32
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• 2019

Research that implements the classification process through Deep Learning algorithm, one of the outstanding human abilities, includes a unimodal model, a multi-modal model, and a multi-modal method using music videos. In this study, the results were better by suggesting a system to analyze each song's spectrum into short samples and vote for the results. Among Deep Learning algorithms, CNN showed superior performance in the category of music genre compared to RNN, and improved performance when CNN and RNN were applied together. The system of voting for each CNN result by Deep Learning a short sample of music showed better results than the previous model and the model with Softmax layer added to the model performed best. The need for the explosive growth of digital media and the automatic classification of music genres in numerous streaming services is increasing. Future research will need to reduce the proportion of undifferentiated songs and develop algorithms for the last category classification of undivided songs.

• The Journal of the Acoustical Society of Korea
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• v.33 no.1
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• pp.81-86
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• 2014

This paper presents a study on the effectiveness of using the spectral and the temporal octave-band order statistics for musical genre classification. In order to represent the relative disposition of the harmonic and non-harmonic components, we utilize the octave-band order statistics of power spectral distribution. Experiments on the widely used two music datasets were performed; the results show that the octave-band order statistics improve genre classification accuracy by 2.61 % for one dataset and 8.9 % for another dataset compared with the mel-frequency cepstral coefficients and the octave-band spectral contrast. Experimental results show that the octave-band order statistics are promising for musical genre classification.

• The Journal of the Korea Contents Association
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• v.18 no.11
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• pp.13-29
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• 2018

An increasing number of people in their lifes have used personal web-casting services as a new type of broadcasting, whose power has grown in the broadcasting market and industry. Nevertheless, limited research concerning personal web-casting has been conducted so far. This research explored consumption structures of personal web-casting users in terms of their genre usage based on the theoretical concept of genre repertoire. And it also examined what determinants have influences on these structures by focusing on as an representative case in South Korea. The findings showed that sensation seeking, motivation for getting information and social presence affect genre repertoire of personal web-casting users. They also indicated that there is a moderating effect of social presence in the relationship between motivation for joy and genre repertoire.