• Korean journal of communication and information
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• v.41
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• pp.145-180
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• 2008

This study tries to test time reallocation hypothesis proposed by Lee(2005) that claims the time use pattern as a whole has changed as new media is introduced-in this case, internet-in our daily lift. It has been pointed out that researches, confined to study whether time use for traditional media is displaced by a new media, have such a limitation as 'media isolationism' and resulted in incoherent conclusions. In order to verify time reallocation hypothesis, which explains the influence of internet use on daily activities with broad perspectives, this research employed two different methods. First, this study analyzed the differences of time use patterns of daily activities and media use behaviors between internet users and non-users by using t-test. Second, logistic regression was used to confirm that the difference of time use pattern between internet users and non-users in many daily activities. The results show that time use pattern for daily activities has reorganized In the most of the age groups. Especially, in the young age groups, time reallocation by internet appeared more obvious than the equivalent old age groups.

• Journal of Digital Convergence
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• v.14 no.1
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• pp.371-377
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• 2016

In the area of mobile game, the job of data analysis is very important. As the mobile game market is being expanded, the characteristics of the market have been so much changed, that the contents updating and marketing strategy should be built on thorough understanding and analysis result of the gamers' needs and their play pattern. Thus the importance of the mobile game management system can not be overemphasized. However, in practice, most of the mobile game companies are small scale, and they have intrinsic problem to provide successful game service to user with a dedicated operating team. To overcome these problems, this paper suggests an efficient mobile game management system based on our already developed mobile game. And the effectiveness of our system is illustrated by our case examples such as prompt response to user question or refund request. Our proposed system also played an important role to plan additional contents update, providing scientific data analysis result on user's play pattern and purchase trend.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.117-140
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• 2019

As the aging phenomenon accelerates and various social problems related to the elderly of the vulnerable are raised, the need for effective elderly care solutions to protect the health and safety of the elderly generation is growing. Recently, more and more people are using Smart Toys equipped with ICT technology for care for elderly. In particular, log data collected through smart toys is highly valuable to be used as a quantitative and objective indicator in areas such as policy-making and service planning. However, research related to smart toys is limited, such as the development of smart toys and the validation of smart toy effectiveness. In other words, there is a dearth of research to derive insights based on log data collected through smart toys and to use them for decision making. This study will analyze log data collected from smart toy and derive effective insights to improve the quality of life for elderly users. Specifically, the user profiling-based analysis and elicitation of a change in quality of life mechanism based on behavior were performed. First, in the user profiling analysis, two important dimensions of classifying the type of elderly group from five factors of elderly user's living management were derived: 'Routine Activities' and 'Work-out Activities'. Based on the dimensions derived, a hierarchical cluster analysis and K-Means clustering were performed to classify the entire elderly user into three groups. Through a profiling analysis, the demographic characteristics of each group of elderlies and the behavior of using smart toy were identified. Second, stepwise regression was performed in eliciting the mechanism of change in quality of life. The effects of interaction, content usage, and indoor activity have been identified on the improvement of depression and lifestyle for the elderly. In addition, it identified the role of user performance evaluation and satisfaction with smart toy as a parameter that mediated the relationship between usage behavior and quality of life change. Specific mechanisms are as follows. First, the interaction between smart toy and elderly was found to have an effect of improving the depression by mediating attitudes to smart toy. The 'Satisfaction toward Smart Toy,' a variable that affects the improvement of the elderly's depression, changes how users evaluate smart toy performance. At this time, it has been identified that it is the interaction with smart toy that has a positive effect on smart toy These results can be interpreted as an elderly with a desire to meet emotional stability interact actively with smart toy, and a positive assessment of smart toy, greatly appreciating the effectiveness of smart toy. Second, the content usage has been confirmed to have a direct effect on improving lifestyle without going through other variables. Elderly who use a lot of the content provided by smart toy have improved their lifestyle. However, this effect has occurred regardless of the attitude the user has toward smart toy. Third, log data show that a high degree of indoor activity improves both the lifestyle and depression of the elderly. The more indoor activity, the better the lifestyle of the elderly, and these effects occur regardless of the user's attitude toward smart toy. In addition, elderly with a high degree of indoor activity are satisfied with smart toys, which cause improvement in the elderly's depression. However, it can be interpreted that elderly who prefer outdoor activities than indoor activities, or those who are less active due to health problems, are hard to satisfied with smart toys, and are not able to get the effects of improving depression. In summary, based on the activities of the elderly, three groups of elderly were identified and the important characteristics of each type were identified. In addition, this study sought to identify the mechanism by which the behavior of the elderly on smart toy affects the lives of the actual elderly, and to derive user needs and insights.

• The Journal of Society for e-Business Studies
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• v.26 no.4
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• pp.133-154
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• 2021

Today smart phone is the most common media with a vehicle called 'application'. In order to understand how media users select applications and build their repertoire, this study conducted two-step approach using big data from smart phone log for 4 weeks in November 2019, and finally classified 8 media repertoire groups. Each of the eight media repertoire groups showed differences in time spent of mobile application category compared to other groups, and also showed differences between groups in demographic distribution. In addition to the academic contribution of identifying the mobile application repertoire with large scale behavioral data, this study also has significance in proposing a two-step approach that overcomes 'outlier issue' in behavioral data by extracting prototype vectors using SOM (Sefl-Organized Map) and applying it to k-means clustering for optimization of the classification. The study is also meaningful in that it categorizes customers using e-commerce services, identifies customer structure based on behavioral data, and provides practical guides to e-commerce communities that execute appropriate services or marketing decisions for each customer group.

• Archives of design research
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• v.18 no.1 s.59
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• pp.135-144
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• 2005

Consumers' awareness of product value, and their product preferences, are becoming increasingly influential in product development, particularly in corporations' efforts in manufacturing products with a competitive edge. Corporations conduct surveys on consumers' product satisfaction and preferences and conduct in-depth studies on consumer needs. They then manufacture products in accordance with the results of these surveys and studies. With the necessity and demand for digital door lock products recently growing, this research sought to explore product competitiveness reinforcement factors that could facilitate market penetration, and to formulate corresponding design strategies. In-depth consumer interviews were also conducted to identify consumer lifestyles and needs. Furthermore, consumer preference images, purchase and use-related patterns, and the status of door lock markets were studied. In the past, to design and manufacture consumer-oriented products, corporations primarily resorted to the improvement of the products' technological features. At present, the users' product preferences and the ways that they use these products are the factors that determine product design. Consumers today tend to adjust their lifestyles according to available products, and prefer products that have greater value in terms of lifestyle and culture. Strategic points for reinforcing competitiveness were presented in this study: first, offering different values that will enhance consumer satisfaction, second, positively developing bio-recognizable methods that will boost consumer preference, third, meeting the consumers' expectations that door lock products should not be mere 'entrance and exit control' systems, but network security systems and fourth, adopting convenient authentication methods backed by advanced technologies.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.338-341
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• 2003

According to a long-term master plan for the implementing of MOMAF's marine environmental informatization, we have developed marine environment portal web site which consists of 7 main-menu and 39 sub-menu including various types of contents (text, image and multimedia) based on RDBMS. This portal site was opened in Oct., 2002 (http://www.meps.info). Also, for the national institutions' distributed DB which is archived and managed respectively the marine chemical data and biological data, the integrated retrieval system was developed. This system is meaningful for the making collaborative use of real data and could be applied for data mining, marine research, marine environmental GIS and making-decisions.

• The Journal of the Korea Contents Association
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• v.9 no.11
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• pp.140-150
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• 2009

Difference of individual character is defined Cerebral Hemispheric Model(CHM) to develop individual intellectual abilities in this paper. Component of preferred online-game is surveyed in accordance with individual character, and investigated for possible applications. An individual is classified with 2 modes of CHM that take charge of intellectual abilities; abilities is character, taste, personality decision-making and behavior patterns; that is closely related to creativity. Difference of game component could be investigated with correlation table of cerebral preference patterns (CPP) that was drawn up with survey. Individual brain preferences (IBP) became clear through preference of individual in the investigation, and suggested concept guide-line to develop other brain preferences. Thus, this study is able to realize from education game to a great variety of contents that base on the development of thinking-faculties as optimization of user preference, can be the basic data of self-development, to improve intellectual faculties as development of individual thinking preference.

• Journal of Korea Game Society
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• v.17 no.3
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• pp.107-116
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• 2017

Sandbox game users can double their satisfaction by re-creating a variety of play patterns. This creative process is due to the expansion of play through 'customizing' and 'action autonomy'. The purpose of this study is to investigate the structural limitations of freedom of online game. In a standalone game, the scalability due to the degree of freedom gives the user a strong motivation for world persistence. On the other hand, in online sandbox games such as MMORPG, it is confirmed that the goal-oriented tendency to gain advantage is the inherent limit of the freedom and expandability of the sandbox game. In this study, it is suggested that the cause and limit of growth of online-based sandbox game can be offset by the optimal solution factor.

• Journal of KIISE
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• v.43 no.7
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• pp.781-785
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• 2016

Learning from human behaviors in the real world is essential for human-aware intelligent systems such as smart assistants and autonomous robots. Most of research focuses on correlations between sensory patterns and a label for each activity. However, human activity is a combination of several event contexts and is a narrative story in and of itself. We propose a novel approach of human activity prediction based on event cognition. Egocentric multi-sensor data are collected from an individual's daily life by using a wearable device and smartphone. Event contexts about location, scene and activities are then recognized, and finally the users" daily activities are predicted from a decision rule based on the event contexts. The proposed method has been evaluated on a wearable sensor data collected from the real world over 2 weeks by 2 people. Experimental results showed improved recognition accuracies when using the proposed method comparing to results directly using sensory features.

• Journal of Service Research and Studies
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• v.10 no.2
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• pp.1-15
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• 2020

As big data become more important socially and economically in recent years, many problems have been derived from the indiscriminate application of big data. Big data are valuable because it can figure out the meaning of informative information hidden within the data. In particular, to predict customer behavior patterns and experiences, structured data that were extracted from Customer Relationship Management (CRM) or unstructured data that were extracted from Social Network Service(SNS) can be defined as a population to interpret the data, during which many errors can occur. However, those errors are usually overlooked. In addition to data analysis techniques, some data, which should be considered in the analysis, are not included in the population and thus do not show any meaningful patterns. Therefore, this study presents the measurement and interpretation of the data generated when the cause of error in the population setting is strong relationship and interaction between people or a person and an object. In other words, it will be shown that if the relationship and interaction are strong, it is important to include data collected from the perspective of user experience and ethnography in the population by comparing various cases of big data application, through which the meaning will be derived and the best direction will be suggested.