• Information Systems Review
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• v.9 no.1
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• pp.85-103
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• 2007

The purpose of this study is to evaluate the performance of collaborative filtering recommender algorithms for better prediction accuracy of the customer's preference. The accuracy of customer's preference prediction is compared through the MAE of neighborhood based collaborative filtering algorithm and correspondence mean algorithm. It is analyzed by using MovieLens 1 Million dataset in order to experiment with the prediction accuracy of the algorithms. For similarity, weight used in both algorithms, commonly, Pearson's correlation coefficient and vector similarity which are used generally were utilized, and as a result of analysis, we show that the accuracy of the customer's preference prediction of correspondence mean algorithm is superior. Pearson's correlation coefficient and vector similarity used in two algorithms are calculated using the preference rating of two customers' co-rated movies, and it shows that similarity weight is overestimated, where the number of co-rated movies is small. Therefore, it is intended to increase the accuracy of customer's preference prediction through expanding the number of the existing co-rated movies.

• PNF and Movement
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• v.18 no.3
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• pp.365-373
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• 2020

Purpose: The COVID-19 pandemic has changed how healthcare is delivered worldwide and has affected the environment of the healthcare. Physical therapy in traditional healthcare systems can be difficult in unusual circumstances, such as the COVID-19 pandemic. Tele-physical therapy, defined as "the delivery of the physical therapy at a distance using electronic information and telecommunication technologies," will be a solution for this healthcare crisis. Thus, in this study, we proposed a mobile application for tele-physical therapy. Methods: This study used the Chrome Browser version 83.0.4 based on the Windows 10 64Bit operating system to use the App Inventor. To operate the mobile application, we used the Samsung Galaxy Note 9. The design of the mobile application was based on the review of a system used in the physical therapy department. Results: The graphical user interface (GUI) of the mobile application was displayed on three screens: selecting a painful joint (1st screen of the GUI); selecting a painful movement of the joint (2nd screen of the GUI); a self-manual therapy method and movie (3rd screen of the GUI). The proposed mobile application showed the stable repeatability of the self-manual therapy movie. Conclusion: The results of this study demonstrated that the proposed mobile application using the App Inventor for android will be able to create easy to use and reliable tele-physical therapy.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.1-18
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• 2022

As digital technology converges into the e-commerce market across industries, online transactions have activated, and the use of online has increased. With the recent spread of infectious diseases such as COVID-19, this market flow is accelerating, and various product information can be provided to customers online. Providing a variety of information provides customers with various opportunities but causes difficulties in decision-making. The recommendation system can help customers to make a decision more effectively. However, the previous research on recommendation systems is limited to only quantitative data and does not reflect detailed factors of products and customers. In this study, we propose an intelligent recommendation system that quantifies the attributes of products and customers by applying text mining techniques to qualitative data based on online reviews and integrates the existing objective indicators of total star rating, sentiment, and emotion. The proposed integrated recommendation model showed superior performance to the overall rating-oriented recommendation model. It expects the new business value to be created through the recommendation result reflecting detailed factors of products and customers.

• Trans-
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• v.14
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• pp.123-155
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• 2023

This study analyzes the characteristics of the social value creation process through the collective appreciation of film. It focuses on the historical development of community cinema in Japan. In modern-day Japan, where digital video is easily accessible and the use of private, personalized media spaces widespread, a sub-culture of collective film appreciation is spreading, as more and more Japanese begin to attend movie screenings in non-commercial theaters. In addition, Japanese community cinema center has begun to integrate and support this viewing experience, which has come to be known as community cinema. A literature review revealed the following characteristics of community cinema. First, local theater screening groups or appreciation groups cooperate with residents to establish and operate movie theaters. Second, these spaces create theoretical and practical participatory learning opportunities that foster understanding of and participation in film culture, through large-scale associations with organizations or institutions that offer viewings. Third, based on collective appreciation, the film culture created through repeated joint viewings produces a social arena in which community can be realized. In these communities film can be put to socially productive uses, such as problem solving.

• Journal of Korea Multimedia Society
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• v.20 no.10
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• pp.1697-1709
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• 2017

This paper aims to investigate the effect of anticipatory motion in Wall E (2008). For the purpose of the study, first of all, an overall discussion on the definition and role of anticipation presented through the related literature review. Based on this, the present study analyzed the functions of anticipatory movements of the main characters, Wall E and EVE in 29 scenes. As a result, this paper found that anticipation is involved in expressions of humanity, thought process, utterance and intonation, the degree of emotion and energy, reinforcement of the character's intention, and biological response within the film. Overall, these findings show that anticipation takes an important part in giving the illusion of life to the characters throughout the movie, which may imply that anticipation can be beneficial for characters with abstract form or limited modality. The ultimate goal of this study is to propose that the animation principles can be used as a tool to analyze character animation and can be applied academically or industrially to other fields such as artificial intelligence.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.75-78
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• 2018

감성 분석은 특정 대상에 대한 의견을 수집하고 분류하는 과정이다. 그러나 자연어에 담김 사람의 주관을 파악하는 일은 어려운 일로써, 기존의 감성 단어 사전이나 확률 모델은 이러한 문제를 해결하기 어려웠으나 딥 러닝의 발전으로 문제 해결을 시도할 수 있게 됐다. 본 논문에서는 사전 학습된 문맥 표현을 한국어 감성 분석에 활용하여 더 높은 성능을 낼 수 있음을 보인다.

• International Commerce and Information Review
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• v.9 no.1
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• pp.427-449
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• 2007

The question of what our cultural goods might have known in a major exporting market, has intrigued investigators since 2000 year. Actually, Maybe Korean cultural assets just didn't have time to get to know International or Asia market. But now, a new euphoria can be tasted, on the lips of the small but growing Korean Contents Mania, as New Korean Wave-Crust begin to welcome the priciest contents from korea. Given Asian's surging population for our entertainment contents-drama, movie, music, character, etc., and the sense of a positive response its newly international market, it is hardly surprising. Now, Korea Wave must play an important roles in our country- economy, business, specially. This paper is seeking in OSMU on Korean Contents in East-North Asian Market, and is developing about Korean Wave study model. and It also points to a different strategy for exporting cultural contents, suggesting it should be effected for model to OSMU.

• International Commerce and Information Review
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• v.1 no.1
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• pp.57-66
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• 2008

The best value proposition for the customers of satellite-DMB (hereinafter referred to as the "S-DMB") business in an environment of fierce competition shall be securing the best killer contents and distribute them in reasonable price as a mobile contents platform provider. In an era of merging the broadcasting with the communication, although many new players tapping into the market with state-of-the-art media such as digital convergence, the key to success in the market is dependent on whether the respective digital contents providers retain competitive digital contents which suit the taste of customers. Considering such market conditions, the purpose of this study is to look over the management examples of Korean S-DMB providers which is carrying out business in digital multi-media market and opening up the market, and to analyze the management strategies of domestic S-DMB companies to be the champion in the market.

• International Journal of Advanced Culture Technology
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• v.8 no.2
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• pp.231-238
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• 2020

Generally, sequential data refers to data having continuity. Text data, which is a representative type of unstructured data, is also sequential data in that it is necessary to know the meaning of the preceding word in order to know the meaning of the following word or context. So far, many techniques for analyzing sequential data such as text data have been proposed. In this paper, four methods of 1d-CNN, LSTM, BiLSTM, and C-LSTM are introduced, focusing on neural network techniques. In addition, by using this, IMDb movie review data was classified into two classes to compare the performance of the techniques in terms of accuracy and analysis time.

• Proceedings of the Korea Information Processing Society Conference
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• 2014.11a
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• pp.1081-1084
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• 2014

최근 들어, 많은 추천시스템들이 연구 되고 있으며, 대부분은 개인 맞춤형 추천 시스템이 연구되고 있다. 기존의 영화추천시스템에서는 희박성의 문제가 제기된다. 본 논문에서는 희박성에 대해 보안하고자, 개인리뷰에 대한 가중치를 활용한다. 그 결과 사용자에게 정보의 제공에 대해 효율성을 높이고, 사용자마다 영화에 대한 리뷰에 따른 감정 및 사용자의 정보들을 반영한 영화추천시스템을 설계 및 구현한다.