• International Journal of Contents
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• v.17 no.1
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• pp.37-53
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• 2021

With the advent of the 5G era, smart phones and communications network technology have progressed, and mobile short video of people's life can be made, Of the new tools of communication, at present, China's social short video industry has shown rapid development, and the most representative of the short video app is Douyin (international version: Tiktok). Under the background of Uses and Gratifications Theory, this study discusse the relationship between Douyin users' preference degree, use motivation, use satisfaction and attention intention. This study divides the content of Douyin video into 10 categories, selects the form of an online questionnaire survey, uses SPSS software to conduct quantitative analysis of 202 questionnaires after screening, and finally draws the following conclusions: (1) The content preference degree of Douyin short video (the high group and low group) is different in users' use motivation, users' satisfaction degree and users' attention intention. ALL results are within the range of statistical significance.(2) Douyin users' video content preference degree has a positive impact on users' use motivation, users' satisfaction degree, and users' attention intention. (3) Douyin users' motivation has a positive impact on users' satisfaction and user' attention intention. (4) Douyin users' satisfaction degree has a positive impact on users' attention intention. Based on the research results, we suggest that Douyin platform pushes videos according to users' preferences. In addition, as the preference degree has an impact on users' motivation, satisfaction degree and attention intention of using the platform, it is important that the platform's focus should to pay attention to the preference degree of users. Collecting users' preferences at the early stage of users' entering the platform is a good way to learn from, and doing a good job of big data collection and management in the later operation.

• Journal of the Korea Society of Computer and Information
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• v.20 no.1
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• pp.29-37
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• 2015

Nowadays, the user-centric application based web 2.0 has replaced the web 1.0. The users gain and provide information by interactive network applications. As a result, traditional approaches that only extract and analyze users' local document operating behavior and network browsing behavior to build the users' preference profile cannot fully reflect their interests. Therefore this paper proposed a preference analysis and indicating approach based on the users' communication information from MicroBlog, such as reading, forwarding and @ behavior, and using the improved PersonalRank method to analyze the importance of a user to other users in the network and based on the users' communication behavior to update the weight of the items in the user preference. Simulation result shows that our proposed method outperforms the ontology model, TREC model, and the category model in terms of 11SPR value.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.36 no.1
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• pp.64-69
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• 2013

In ubiquitous computing, shared environments adjust themselves so that all users in the environments are satisfied as possible. Inevitably, some of users sacrifice their satisfactions while the shared environments maximize the sum of all users' satisfactions. In our previous work, we have proposed social welfare functions to avoid a situation which some users in the system face the worst setting of environments. In this work, we consider a more direct approach which is a preference based clustering to handle this issue. In this approach, first, we categorize all users into several subgroups in which users have similar tastes to environmental parameters based on their preference information. Second, we assign the subgroups into different time or space of the shared environments. Finally, each shared environments can be adjusted to maximize satisfactions of each subgroup and consequently the optimal of overall system can be achieved. We demonstrate the effectiveness of our approach with a numerical analysis.

• Journal of the Korean Data and Information Science Society
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• v.18 no.3
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• pp.619-628
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• 2007

This study is devoted to suggesting the norm of detection abnormal users who are inferior to the other users in the recommender system compared with estimation accuracy. To select the abnormal users, we propose the pre-filtering method by using the preference ratings to the item rated by users. In this study, the experimental result shows the possibility of detecting the abnormal users before the process of preference estimation through the prediction algorithm. And It will be possible to improve the performance of the recommender system by using this detecting norm.

• Journal of the Korean Data and Information Science Society
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• v.18 no.3
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• pp.659-668
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• 2007

Collaborative filtering approach for recommender systems are now widely applied in e-commerce to assist customers to find their needs from many that are frequently available. this approach makes recommendations for users based on the opinions to similar users in the system. But this approach is opened to users who present their preference to items or acquire the preference information form other users, noise in the system makes significant problem for accurate recommendation. In this paper, we analyze the relationship between the standard deviation of preference ratings for each user and the estimated ratings of them. The result shows that the possibility of the pre-filtering condition which detecting the factor of bad effect on the prediction of user's preference. It is expected that using this result will reduce the possibility of bad effect on recommender systems.

• Journal of the Korean Home Economics Association
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• v.42 no.3
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• pp.195-209
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• 2004

The purpose of this study was 1) to examine the usage of mobile internet by cell phone or palm pilot, etc., 2) to analyze mobile users' lifestyles, 3) to examine preferred fashion services according to users' lifestyles and 4) to investigate service satisfaction and preference with the mobile internet. 193 university students in Seoul were randomly selected as subject. The data was analyzed using descriptive statistics (i.e., percentage, frequency), factor analysis, cluster analysis and ANOVA. The results of the study were as follows: first, most mobile users spent 10 min a day for using the mobile internet (i.e., short message service) mainly in transportation vehicles. Secondly, five factors in the mobile users' lifestyle were named as: 'surfer', 'absorber', 'expert', 'accepter' and 'enthusiast'. Thirdly, two factors in the preferences of fashion service on mobile internet were 'customized information service' and 'ordinary information service'. Fourthly, according to the internet lifestyle, mobile users were classified into three groups: 'mania group', 'follower group', and 'veteran group'. The mania group was the highest group in mobile service satisfaction and service preference. Marketing implications are discussed for the successful mobile business in clothing and textile industry.

• Journal of KIISE
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• v.44 no.6
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• pp.621-627
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• 2017

Collaborative filtering is a technique that effectively recommends unrated items for users. Collaborative filtering is based on the similarity of the items evaluated by users. The existing top-N recommendation methods are based on pair-wise and list-wise preference models. However, these methods do not effectively represent the relative preference of items that are evaluated by users, and can not reflect the importance of each item. In this paper, we propose a new method to represent user's latent preference by combining an existing preference model and the notion of inverse user frequency. The proposed method improves the accuracy of existing methods by up to two times.

• Journal of the Korean Society of Industry Convergence
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• v.6 no.1
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• pp.57-64
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• 2003

Nowadays, there are many problems of traffic and parking in residential areas. This study begins analysis the parking situations in apartment complex. It originated from understanding of the parking preference of users about underground and ground parking lots. The method of this study is based on field survey of parking demand and thoughts of users of underground parking lot. There are so many parking problems in apartment complex that is due to the absence of parking demand data. So the goal of this study is to provide a solution of parking problems in apartment complex through understanding of the actual condition of parking problems, the preference and the reason of users about underground parking lot in apartment complex.

• Journal of the Korea Society of Computer and Information
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• v.21 no.9
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• pp.57-63
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• 2016

The purpose of the study is to investigate the preference by emoticon types according to the gender of sender, emotion types of message and intimacy with the recipient. Results show that women mostly prefer to use dynamic and imaged emoticon than men. However, the preference of using text messages increases when both men and women express uncomfortable emotion. Especially, when users send family messages, they tend to prefer for text message. And when users send close friends messages, the preference for dynamic and imaged emoticon is high. When users send distant friends messages, the similar tendency is shown regardless of emotion. These results can provide the information to use emoticon in the filed of education and take advantage in digital education and mobile education.

• Journal of Korea Game Society
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• v.10 no.2
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• pp.21-27
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• 2010

This paper is an analysis of the domestic game users preference for physical interactive game consol-Nintendo Wii. The on-line game is the biggest share in korean game market and the 20's is the laregest generation in domestic game users. We conducted the surveys and group discussion to find out how the 20's game users prefer the new console and new type games. I hope the result of survey will assist the development of new game console and new game type.