• Journal of Digital Convergence
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• v.12 no.6
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• pp.325-332
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• 2014

It is generally accepted that classification accuracy is affected by the number of learning documents, but there are few studies that show how this influences automatic text classification. This study is focused on evaluating the deviation-based classification model which is developed recently for genre-based classification and comparing it to other classification algorithms with the changing number of training documents. Experiment results show that the deviation-based classification model performs with a superior accuracy of 0.8 from categorizing 7 genres with only 21 training documents. This exceeds the accuracy of Bayesian and SVM. The Deviation-based classification model obtains strong feature selection capability even with small number of training documents because it learns subject information within genre while other methods use different learning process.

• Journal of Korea Entertainment Industry Association
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• v.15 no.2
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• pp.83-97
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• 2021

This study started with curiosity about theatre without its three elements and would reveal its possibility through performance and experiment and promote the expansion of each element and the development of a new form at the same time. After the occurrence of COVID-19, theatre has come up against a big limitation of contact-free, untact communication due to its inherent characteristic of 'presence.' For the survival of theatre in the rapidly changing world, it is desperately necessary to check the existing performance method and to be concerned about its development for the future. Thus, this researcher started from a more fundamental exploration of theatre focused on an "experiment of theatre without its three elements" and would sort out the three elements (actors, audience, and a play) from a macroscopic perspective. Also, the researcher would investigate the impacts of these elements on the performance and the possibility of theatre even after removing the elements through performance and experiment. This study consists of one performance and two experiments and is based on the interviews and progress details conducted by the planner and experimenter and the survey with the experiment participants. The significance of this study is its reflection on the essence of the genre, theatre, and the roles of all elements constituting that, not from a narrow perspective that would simply define the concepts of the elements but through the expansion and change of them. Furthermore, hopefully, it will be connected to the discovery of a new theatrical format that has not been considered through its combination with another genre.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.4
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• pp.877-885
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• 2011

A collaborative filtering(CF) is the most widely used technique in recommender system. However, CF has sparsity and scalability problems. These problems reduce the accuracy of recommendation and extensive studies have been made to solve these problems, In this paper, we proposed a method that uses a weight so as to solve these problems. After creating a user-item matrix, the proposed method analyzes information about users who prefer the item only by using data with a rating over 4 for enhancing the accuracy in the recommendation. The proposed method uses information about the genre of the item as well as analyzed user information as a weight during the calculation of similarity, and it calculates prediction by using only data for which the similarity is over a threshold and uses the data as the rating value of unrated data. It is possible simultaneously to reduce sparsity and to improve accuracy by calculating prediction through an analysis of the characteristics of an item. Also, it is possible to conduct a quick classification based on the analyzed information once a new item and a user are registered. The experiment result indicated that the proposed method has been more enhanced the accuracy, compared to item based, genre based methods.

• Journal of Broadcast Engineering
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• v.26 no.5
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• pp.621-642
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• 2021

In this paper, the subjective video quality assessment of the content quality was to examine by the assessors about the three content quality of HD, Up-scaling UHD, 4K UHD Native that is currently broadcasted. The comparative assessment was conducted using three types of TV sets, 55, 65, 75 inches, at a distance of 2.5 meters which is the distance of watching TV in general households. Among the participants who took part in the video quality evaluating experiment and the questionnaire survey, the answering data of the final 169 persons were adopted after removing the data of 4 persons who answered inadequately in the evaluation of the video quality. The effects of gender, preference of program genre, size of TV sets were analyzed statistically using SPSS 25.0 analysis package. In addition to these, the objective video quality assessment through the measuring instrument was performed, and compared with the results of subjective video quality assessment.

• Journal of English Language & Literature
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• v.60 no.2
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• pp.269-293
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• 2014

Written as her last collaboration with the Provincetown Players, Susan Glaspell's The Verge is an exceptional play in that its formal experiment and modernist theme are clear of her general modernist ambivalence which combines a uniquely American and feminist expression of the modernist spirit with rather conventional forms. Following critics' brief and generalizing comments on the play's protagonist embodying modernist formalism and alienation, this paper offers a full and concrete survey detailing the tenets and the slogans of Modernism inlaid in the play. Its main argument is that Glaspell strategically deployed the metaphysics of egoism, anarchic hostility to the collectiveness of bourgeois society, and formalist preoccupation in Modernism in representing a female egoist's longing for a new order of society, illustrating an intersection between Modernism and feminism. It concludes that The Verge is an extremely rare case of modernist literature where a play, allegedly the least modernist genre of all according to Christopher Innes, exemplifies the "eloquent critical acts entangled in the creative work" which Michael Levenson lists as a distinct feature of modernist texts.

• Journal of Broadcast Engineering
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• v.26 no.3
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• pp.308-320
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• 2021

Conventional image quality studies have been focused on 'naturalness' and has relied on memory color. Memory colors are mainly formed for familiar objects with prior experience, and the more faithfully these memories are reflected, the more naturalness of the reproduced image quality increases. In particular, the brightness and saturation of memory colors play an important role in increasing the preference of image quality as well as naturalness. Therefore, in the case of existing image quality studies, image quality characteristics were studied focusing on natural objects and people with memory. We extracted representative images of each genre (sports, documentaries, news, entertainment and music, and movies), adjusted the brightness, contrast, and saturation of each image, and conducted an experiment to evaluate perceived quality. Based on situational context, the results of this classification indicated that genres of television content can be divided into two categories: proximate and indirect experiences. Proximate experience best characterizes outdoor sports, dramas, and nature documentaries, where their image qualities have shown to have a strong correlation with brightness and contrast. On the other hand, indirect experience best characterizes news, music shows and SF/action movies. The image quality perception for indirect experiences was shown to be closely related to and optimized by contrast and saturation.

• Journal of Korea Game Society
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• v.9 no.2
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• pp.23-28
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• 2009

There are a lot of games which have good benefits in the game genre such as serious game. In this paper we implement an serious game for increasing intensive power by calculating the index of the intensive power based on EEG signal. First we explain the definition of the EEG and the classification of the brainwaves and we depict the method for increasing the intensive power. Then we apply the index of the intensive power to the game production to train the intensive power. At last we make an experiment on the effect of an game which increases the intensive power and the analysis shows the increase of the intensive power.

• The Journal of the Korea Contents Association
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• v.16 no.3
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• pp.162-170
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• 2016

Xavier Dolan delves into maternal instinct and sexual identity and the attempt and experiment of his movies are not difficult to understand and not unfamiliar. He communicates with audience through pastiche and self-reflexivity, rather than disassembling and destruction of style and form of existing films. Pastiche is the intertextuality between familiar genres such as film, poem, fashion, music, painting, etc. His films shows the characteristics of postmodernism, which include genre over, de-subjectivity, interest in public culture, and representation of nostalgia. This study recognizes anew the present of postmodernism gradually going out of fashion and analyzes the characteristics of postmodernism and repeated motif in his movies. This study also analyzes Xavier Dolan's interest in social minority and allegorian characteristics through characters appearing in his movies.

• Journal of Korea Multimedia Society
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• v.10 no.5
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• pp.559-568
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• 2007

Anchor-person scene detection is of significance for video shot semantic parsing and indexing clues extraction in content-based news video indexing and retrieval system. This paper proposes an efficient algorithm extracting anchor ranges that exist in sports news video for unit structuring of sports news. To detect anchor person scenes, first, anchor person candidate scene is decided by DCT coefficients and motion vector information in the MPEG4 compressed video. Then, from the candidate anchor scenes, image processing method is utilized to classify the news video into anchor-person scenes and non-anchor(sports) scenes. The proposed scheme achieves a mean precision and recall of 98% in the anchor-person scenes detection experiment.

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.45-52
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• 2022

With the development of artificial intelligence analysis methods, especially machine learning, various fields are widely expanding their application ranges. However, in the case of classical music, there still remain some difficulties in applying machine learning techniques. Genre classification or music recommendation systems generated by deep learning algorithms are actively used in general music, but not in classical music. In this paper, we attempted to classify opera among classical music. To this end, an experiment was conducted to determine which criteria are most suitable among, composer, period of composition, and emotional atmosphere, which are the basic features of music. To generate emotional labels, we adopted zero-shot classification with four basic emotions, 'happiness', 'sadness', 'anger', and 'fear.' After embedding the opera libretto with the doc2vec processing model, the optimal number of clusters is computed based on the result of the elbow method. Decided four centroids are then adopted in k-means clustering to classify unsupervised libretto datasets. We were able to get optimized clustering based on the result of adjusted rand index scores. With these results, we compared them with notated variables of music. As a result, it was confirmed that the four clusterings calculated by machine after training were most similar to the grouping result by period. Additionally, we were able to verify that the emotional similarity between composer and period did not appear significantly. At the end of the study, by knowing the period is the right criteria, we hope that it makes easier for music listeners to find music that suits their tastes.