• Journal of the Korea Society of Computer and Information
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• v.23 no.2
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• pp.117-123
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• 2018

This article is to investigate the possibility that project-based classes introducing mobile phones can replace the monotony of traditional classes led by teachers as well as they can encourage students to take active part in the classes to some extent. The students in groups choose a genre for their own video projects (e.g., movie, drama, news, documentary, and commercial) and produce the video contents using a mobile phone for presentation made at the end of a semester. In the sense that the students are allowed to do video-based mobile phone projects, they can work independently outside of class, where time and space are more flexible and students are free from the anxiety of speaking or acting in front of an audience. A mobile phone project consists of around five stages done both in and outside of the classroom. All of these stages can be graded independently, including genre selection, drafting of scripts, peer review and revision, rehearsals, and presentation of the video. Feedback is given to students. After the presentation, students filled out a survey questionnaire sheet devised to analyze students' responses toward preferences and level of difficulty of the project activity. Finally, proposals are made for introduction of a better mobile phone-based project classes.

• The Journal of Society for e-Business Studies
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• v.25 no.2
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• pp.49-63
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• 2020

The accurate prediction of box office in the early stage is crucial for film industry to make better managerial decision. With aims to improve the prediction performance, the purpose of this paper is to evaluate the use of machine learning methods. We tested both classification and regression based methods including k-NN, SVM and Random Forest. We first evaluate input variables, which show that reputation-related information generated during the first two-week period after release is significant. Prediction test results show that regression based methods provides lower prediction error, and Random Forest particularly outperforms other machine learning methods. Regression based method has better prediction power when films have small box office earnings. On the other hand, classification based method works better for predicting large box office earnings.

• Journal of the Korean Society of Earth Science Education
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• v.8 no.2
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• pp.164-182
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• 2015

The purpose of this study was investigated the perceptions and expectations of science gifted elementary students in the laboratory-based science learning. For the purpose of this study, semi-structured interviews were conducted with 20 science gifted elementary students in J city. The question of the interview is constructed with perception and expectation of science gifted elementary students in divided with 4steps of understanding of lesson object, planning experiment, performing experiment and drawing conclusion in laboratory-based science learning and an attitude for science. The interview is progressed per individual and all the content of the interview is recorded. The result of this research is as follows. The science gifted elementary students have a wish for building an assumption and expectation and planning an experiment with discussion more than following the textbook and teacher present. In the step of the experiment, they wanted general more discussion of their own activities rather than teacher's instruction and they wanted teacher's instruction and they wanted teacher's mediation conflicts within small groups and comments for students' experiment results. The science gifted elementary students wish to open a science lab, which man who likes science can go and come freely and to study with friends who have a same interest to make a theme. And from top to bottom they want to test autonomous and ask to salute like a representative experiment of teacher. And they ask to have a chance to test individually and want to see a movie related to an experiment before doing an experiment. Like this, it presents that the scientifically gifted elementary students want to do an experiment what they can, want to have a class which can plan and can do an experiment by themselves through discussion with the unit more than following explanation of a teacher and a textbook without condition.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.284-286
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• 2021

With the continuous development of the Internet and digital, platforms are emerging to store large amounts of media data and provide customized services to individuals through online. Companies that provide these services recommend movies that suit their personal tastes to promote media consumption. Each company is doing a lot of research on various algorithms to recommend media that users prefer. Movies are divided into genres such as action, melodrama, horror, and drama, and the film's audio (music, sound effect, voice) is an important production element that makes up the film. In this research, based on movie trailers, we extract audio for each genre, check the commonalities of audio for each genre, distinguish movie genres through supervised learning of artificial intelligence, and propose a utilization method for generating metadata in the future.

• Journal of Digital Convergence
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• v.19 no.3
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• pp.279-285
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• 2021

This paper criticized that online classes during the Covid-19 period were centered on knowledge and information education, and sought ways to improve empathy as a way to improve students' sociality. The teaching-learning process was designed around the movie <(500) Days of Summer> which has the theme and story of parting and growth. On this paper the stage of empathy was divided into three stages, recognize-into, feeling-into, emotional-transaction stage. In particular, considering the process of transitioning from emotional empathy to behavioral empathy as the key to communication education, the class was designed in five stages, with an expression stage between the feeling-into stage and the emotional-transaction stage. This course is possible when learners sympathize with the work itself and reflect on their own narrative, so literary therapeutic was used, and students's response statements were collected to prove that this process is meaningful for improving empathy. In this article, the class was designed for the movie <(500) Days of Summer>, but this teaching-learning model can be applied to other contemporary film texts.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.457-466
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• 2004

Recommendation is to offer information which fits user's interests and tastes to provide better services and to reduce information overload. It recently draws attention upon Internet users and information providers. The collaborative filtering is one of the widely used methods for recommendation. It recommends an item to a user based on the reference users' preferences for the target item or the target user's preferences for the reference items. In this paper, we propose a neural network based collaborative filtering method. Our method builds a model by learning correlation between users or items using a multi-layer perceptron. We also investigate integration of diverse information to solve the sparsity problem and selecting the reference users or items based on similarity to improve performance. We finally demonstrate that our method outperforms the existing methods through experiments using the EachMovie data.

• The Journal of Korean Academic Society of Nursing Education
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• v.24 no.4
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• pp.376-390
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• 2018

Purpose: The purpose of this study was to (a) synthesize nursing education literature using a smartphone for Korean nursing college students based on Whittemore and Knafl's integrative five-step review method and to (b) evaluate the quality appraisal of each article using Gough's weight of evidence. Methods: Articles published in Korea were identified through electronic search engines and scholarly websites using a combination of three search terms, including nursing student, smartphone, and education. Scientific, peer-reviewed articles in nursing education for Korean college nursing students, written in Korean or in English, and published between January 2000 and May 2018 were included in this review. Thirteen papers met the inclusion criteria and had above average ratings in quality appraisals. Results: Three characteristics related to nursing education using a smartphone were derived: (a) as a familiar media, motivating learning and enabling self-directed learning, (b) for the purpose of education or evaluation utilizing the educational movie of application, and (c) the iterative exercise of smartphone usage reinforces student learning. Conclusion: Smartphone use is an effective tool for improving nursing knowledge and skills for nursing college students in nursing education. Future research is needed to standardize smartphone applications across schools for nursing education.

• Journal of information and communication convergence engineering
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• v.20 no.4
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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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.537-542
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• 2021

Smart TVs provide a variety of services and information compared to existing TVs based on the Internet. In order to provide more personalized services or information, it is necessary to analyze users' viewing patterns and provide customized services or information based on them. The proposed system receives the user's TV viewing pattern, analyzes it, and recommends a TV program or movie as customized information to the user. For this, the system was constructed with a preprocessor and a deep learning model. The preprocessor refines the name of the TV program watched by the user, the date the TV program was watched, and the watched time. Then, the multi-attribute LSTM model trains the refined data and performs prediction.The proposed system is a system that provides customized information to users, and is believed to be a leading technology in digital convergence that combines existing IoT technology and deep learning technology.

• Journal of the Korea Society of Computer and Information
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• v.26 no.10
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• pp.157-165
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• 2021

Recently, studies using deep learning to analyze a large amount of text are being actively conducted. In particular, a pre-trained language model that applies the learning results of a large amount of text to the analysis of a specific domain text is attracting attention. Among various pre-trained language models, BERT(Bidirectional Encoder Representations from Transformers)-based model is the most widely used. Recently, research to improve the performance of analysis is being conducted through further pre-training using BERT's MLM(Masked Language Model). However, the traditional MLM has difficulties in clearly understands the meaning of sentences containing new words such as newly coined words. Therefore, in this study, we newly propose NTM(Newly coined words Target Masking), which performs masking only on new words. As a result of analyzing about 700,000 movie reviews of portal 'N' by applying the proposed methodology, it was confirmed that the proposed NTM showed superior performance in terms of accuracy of sensitivity analysis compared to the existing random masking.