• Journal of Distribution Science
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• v.13 no.8
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• pp.73-80
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• 2015

Purpose - This study's objective is to analyze the content of the communications between users and producers based on the construal level theory. User generated content refers to content created in an online-based service where users and producers communicate interactively with each other. In a user generated content platform, the messages sent and received between the many players, the users and producers who use the content, may be analyzed at the psychological level based on construal level theory. Research design, data, and methodology - This study gathered user and producer participation through a snow-bowling sampling method. The data analyzed includes 125 video clips and 2,912 comments. The period of the data collection was from September 2014 to December 2014. The collected data was analyzed using a t-test and two-way ANOVA. Results - This study obtained the following research results. First, users who were a short social distance from producers responded to user participatory activities stated in concrete language rather than abstract language. In contrast, users who were at a longer social distance from producers tended to respond to the content requesting user participation through abstract language. Second, if users and producers were at a short social distance from each other, user preference increased more when a producer response to user participation was expressed concretely rather than when it was expressed abstractly. In contrast, if the users were at a longer social distance, users' preferences increased more when producer response was expressed abstractly rather than when it was expressed concretely. Conclusion - This study found that the effect of suitability, in which the social distance and the content were in congruence at the construal level, could be observed. Therefore, based on this, academic and practical implications were drawn. The three main insights of the study are as follows. First, firms can use psychological factors to analyze the message content of users in their distribution platforms. This study reveals managerial implications for marketing managers who want to take make use of this analysis of user and producer communications. This study indicates that the main factors include the concrete and abstract scores and social distance between users and producers. Second, we also provide the strategic guidelines to maximizing user preferences and other outcomes. The main dependent variable in this study is the user preference shift; the variable increases through the congruence effect; and the construal level is determined by the social distance between the users and producers and the type of producer response. The outcomes here from users can be utilized to develop several systemic strategies. One process to use the outcomes could be: (1) firms could measure the users and producers social distance; (2) calculate the concreteness or abstractness of the messages; and, (3) predict the user preference outcomes by the congruence between user and producer social distance and the abstractness or concreteness of the message content.

• Journal of the Ergonomics Society of Korea
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• v.28 no.4
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• pp.147-154
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• 2009

The tactical computer is currently being developed and installed in armored vehicles and tanks for reinforcement. With the tactical computer, Korea Army will be able to grasp the deployment status of our forces, enemy, and obstacles under varying situations. Furthermore, it makes the exchange of command and tactical intelligence possible. Recent studies showed that the task performance is greatly affected by the user interface. The U.S. Army is now conducting user-centered evaluation tests based on C2 (Command & Control) to develop tactical intelligence machinery and tools. This study aims to classify and regroup subordinate menu functions according to the user-centered task performance for the Korea Army's tactical computer. Also, the research suggests an ergonomically sound layout and size of main touch buttons by considering human factors guidelines for button design. To achieve this goal, eight hierarchical subordinate menu functions are initially drawn through clustering analysis and then each group of menu functions was renamed. Based on the suggested menu structure, new location and size of the buttons were tested in terms of response time, number of error, and subjective preference by comparing them to existing ones. The result showed that the best performance was obtained when the number of buttons or functions was eight to conduct tactical missions. Also, the improved button size and location were suggested through the experiment. It was found in addition that the location and size of the buttons had interactions regarding the user's preference.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.4
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• pp.85-96
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• 2022

Personalized recommendation technology is one of the most important technologies in electronic commerce environment. It helps users overcome information overload by suggesting information that match user's interests. In e-commerce environment, both mobile device users and smart device users have risen dramatically. It creates new challenges. Our method suggests product information that match user's device interests beyond only user's interests. We propose a device-centered personalized recommendation method. Our method uses both purchase and share behavior for user's devices interests. Moreover, it considers data type preference for each device. This paper presents a new recommendation method and algorithm. Then, an e-commerce scenario with a computer, a smartphone and an AI-speaker are described. The scenario shows our work is better than previous researches.

• Archives of design research
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• v.20 no.3 s.71
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• pp.203-214
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• 2007

This study proposes an information retrieval method reflecting the user's preferences based on the fuzzy set theory to develop information contents which support pedestrian's navigation. Firstly, the research evaluated subjects' preferences on commercial spaces set to a hypothetical destination. Also it surveyed the causal relationship between the visual characteristics and the emotional characteristics to propose methods of Navigation Knowledge Base (NKB). The NKB was composed of three elements; 1. the correlation model between emotional characteristics, 2. the causal relationship between visual characteristics and emotional characteristics, 3. the transformation model between visual characteristics and the physical characteristics. Secondly, this study classified the pedestrian's destination search into 4 types with his or her preferences and the time conditions limited during navigation. For each type it presented the Destination Search Algorithm (DSA). Finally, the research simulated the destination search in 4 navigation types using NKB and DSA and verified the availability of the information retrieval method reflecting pedestrian's preferences. In conclusion, the proposed information search method will be applied to reflect the user's preferences to develop information appliances.

• Journal of Korea Multimedia Society
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• v.10 no.10
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• pp.1356-1366
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• 2007

Many personalized Services that provide users with adaptive information according to users' requirements and preferences have been researched and developed. However, existing approaches are difficult to share a user's information among heterogeneous services because these approaches manage users' preferences in a single system. In this paper, we propose a user preference sharing model based on the Semantic Web as a solution to resolve the problem. Our model enables user preferences to be described and shared over service-specific ontologies which are affected by the feature of each service. Our model is analyzed and evaluated with an implementation of the middleware that supports our model. Our approach has the advantage of providing more efficient personalized services than existing approaches because it can describe users' preferences centering around each service and share these information among heterogeneous personalized services.

• Journal of KIISE:Software and Applications
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• v.32 no.6
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• pp.542-553
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• 2005

Recommendation systems analyze user preferences and recommend items to a user by predicting the user's preference for those items. Among various kinds of recommendation methods, collaborative filtering(CF) has been widely used and successfully applied to practical applications. However, collaborative filtering has two inherent problems: data sparseness and the cold-start problems. If there are few known preferences for a user, it is difficult to find many similar users, and therefore the performance of recommendation is degraded. This problem is more serious when a new user is first using the system. In this paper we propose a method of integrating additional feature information of users and items into CF to overcome the difficulties caused by sparseness and improve the accuracy of recommendation. In our method, we first fill in unknown preference values by using the probability distribution of feature values, then generate the top-N recommendations by applying collaborative filtering on the modified data. We call this method of filling unknown preference values as data blurring. Several experimental results that show the effectiveness of the proposed method are also presented.

• The Journal of the Korea Contents Association
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• v.2 no.1
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• pp.113-119
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• 2002

E-Biz. system must provide convenient and easy interface, efficient functions, and provides information and contents satisfying customers. To do this, many kinds of studies are being advanced actively about E-Biz. system using intelligent agent technology and efficient E-Biz. strategy. Also E-Biz. system score a lot of information and contents to get a efficient business activities and relationships between a company arid customers. To effectively adopt individual customer's preference and actively adapt change of business situation, we may consider individual user characteristics and emotion. This paper suggests E-Biz. system using intelligent agent technology based on user characteristics and emotion. This system can provide convenient user interface and improve customer royalty. In the results, it is found that proposed system is more efficient than existing systems about customer's preference.

• Korean Institute of Interior Design Journal
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• v.18 no.6
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• pp.194-201
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• 2009

The purpose of this study is to develop basic data for the efficient space plan of the Department Store focusing on users by survey of preference to methods of plan considering the functional phase, the economical phase and the adaptable phase. The results are as follows : First, we could know that users had the low degree of satisfaction to the adaptable phase of space plan for Supporting Facilities in department stores at the present time. Second, we must have the appropriate space size by using structure, doors and windows for user's satisfaction. This is the method of plan considering the functional phase for Supporting Facilities. And we could think that the methods of using the center flow plan and the arrangement of two or three facing are good for user's satisfaction. Third, it will be efficient plan if we find methods to be cleaned the structure easily and to be changed and repaired the system furniture easily for management. that methods are to be considered the economical phase for Supporting Facilities. Forth, methods of plan considering the adaptable phase are to change the size of space by using the movable type furniture and the form of space by changing structure.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.24 no.4
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• pp.115-131
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• 2013

The goal of this study is to analyze use patterns of library collections using circulation statistics of academic library user's. For this purpose, the 264,804 circulation-related data of A-academic library which were occurred between March 2012 and February 2013 were collected and used. Five patterns of common user group (undergraduate, graduate students, professors, staffs, the others users) are identified for this study. Gross circulation statistics was analyzed and compared for different users groups and for different subjects. And based on these analysis results, author understood degree of collection use by subject, degree of collection use by user groups, latest materials preference in collection use by subject, latest materials preference in collection use by user groups.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.310-315
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• 2007

When a mail was given to users, each user's response could be different according to his or her preference. This paper presents a solution for this situation by constructing a u!;or preferred ontology for anti-spam systems. To define an ontology for describing user behaviors, we applied associative classification mining to study preference information of users and their responses to emails. Generated classification rules can be represented in a formal ontology language. A user preferred ontology can explain why mail is decided to be spam or non-spam in a meaningful way. We also suggest a nor rule optimization procedure inspired from logic synthesis to improve comprehensibility and exclude redundant rules.