• Journal of Korea Trade
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• v.26 no.3
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• pp.1-22
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• 2022

Purpose - Social media platforms have presented individuals with an opportunity to create and maintain their social relationship through the use of social media services. However, such social relationship has a negative influence on users' interest in social media. Design/methodology - Using structural equation modeling, this study seeks to examines the effects of different social media conflicts (individual and social conflicts) on users' psychological internal state, especially user apathetic behavior Findings - The findings confirm that, among social media conflicts, social-related conflict, especially social interaction overload has a negative effect on cognitive resonance, while individual conflict has the highest effect on cognitive dissonance. Also, cognitive dissonance has a much greater effect than cognitive resonance on user resistance, this means that users' negative perception of social media has a greater influence on their resistance. Lastly, user's resistance was found to have a positive influence on user's apathetic behavior. Originality/value - In other to capture social media Apathetic behavior, this study focus on social media conflict perspective, which includes social-related conflict and individual conflict, which are found to influence users' internal states towards social media and further induce social media behavior. This study is unique because it is among the first to explore social media apathetic behavior by focusing on the influence of both external social media conflict and internal state. Also, this study proposed that social related conflict has a higher negative influence on WeChat user than individual related conflict.

• Review of KIISC
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• v.5 no.2
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• pp.32-48
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• 1995

Our paper describes an Intrusion Detection Parallel System(IDPS) which detects an anomaly activity corresponding to the actions that interaction between near detection events. IDES uses parallel inductive approaches regarding the problem of real-time anomaly behavior detection on rule-based system. This approach uses sequential rule that describes user's behavior and characteristics dependent on time. and that audits user's activities by using rule base as data base to store user's behavior pattern. When user's activity deviates significantly from expected behavior described in rule base. anomaly behaviors are recorded. Observed behavior is flagged as a potential intrusion if it deviates significantly from the expected behavior or if it triggers a rule in the parallel inductive system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.5
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• pp.121-127
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• 2008

User needs in residential environment have very complicated and variety connection with others. u-home system for the near future is need to be combined acceptance of exist user needs as well as needs on new technology relating with u-Home. The study proposes a User Behavior Analysis Framework - UBAF for applying the user needs to the system more efficiently and developing the system by classifying patterns for the needs based on date of user behavior analysis. UBAF is a developing framework getting the basic idea of combining system modeling methods on SE and user modeling methods considering on HCI. It will be applicable to develop the system with core user behaviors by applying a standard way on u-Home. For example, the study transforms information into knowledge the system modeling and user modeling with analyzing a scenario for indoor temperature controlling on u-Home.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.3055-3073
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• 2019

In this paper, a new user identification method is presented using real environmental human-computer-interaction (HCI) behavior data to improve method usability. User behavior data in this paper are collected continuously without setting experimental scenes such as text length, action number, etc. To illustrate the characteristics of real environmental HCI data, probability density distribution and performance of keyboard and mouse data are analyzed through the random sampling method and Support Vector Machine(SVM) algorithm. Based on the analysis of HCI behavior data in a real environment, the Multiple Kernel Learning (MKL) method is first used for user HCI behavior identification due to the heterogeneity of keyboard and mouse data. All possible kernel methods are compared to determine the MKL algorithm's parameters to ensure the robustness of the algorithm. Data analysis results show that keyboard data have a narrower range of probability density distribution than mouse data. Keyboard data have better performance with a 1-min time window, while that of mouse data is achieved with a 10-min time window. Finally, experiments using the MKL algorithm with three global polynomial kernels and ten local Gaussian kernels achieve a user identification accuracy of 83.03% in a real environmental HCI dataset, which demonstrates that the proposed method achieves an encouraging performance.

• Journal of the Korean Society for Library and Information Science
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• v.35 no.3
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• pp.173-189
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• 2001

This paper presents a framework for observable behavior that can be used as a basis for user modeling, and it reports the results of a pair of user studies that examine the joint utility of two specific behaviors. User models can be constructed by hand, or they can be teamed automatically based on feedback provided by the user about the relevance of documents that they have examined. By observing user behavior, it is possible to obtain implicit feedback without requiring explicit relevance judgments. Four broad categories of potentially observable behavior are identified : examine, retain, reference, and annotate, and examples of specific behaviors within a category are further subdivided based on the natural scope of information objects being manipulated . segment object, or class. Previous studies using Internet discussion groups (USENET news) have shown reading time to be a useful source of implicit feedback for predicting a user's preferences. The experiments reported in this paper extend that work to academic and professional journal articles and abstracts, and explore the relationship between printing behavior and reading time. Two user studies were conducted in which undergraduate students examined articles or abstracts from the telecommunications or pharmaceutical literature. The results showed that reading time can be used to predict the user's assessment of relevance, that the mean reading time for journal articles and technical abstracts is longer than has been reported for USENET news documents, and that printing events provide additional useful evidence about relevance beyond that which can be inferred from reading time. The paper concludes with a brief discussion of the implications of the reported results.

• Journal of Digital Contents Society
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• v.16 no.3
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• pp.493-501
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• 2015

This study is to observe the correlation between user properties and user behavior on the mobile game, one of the most prominent digital contents with the most mutual interaction. Among various factors affecting on behaviors of game users, the user properties itself was accentuated, and the effect of individual and psychological quality on the use of game was evaluated. The user properties were mainly categorized into five factors of "interpersonal relationship", "level of game skill", "inclination of innovation", "self-esteem", and "competitive spirit", and the use behavior of game was categorized mainly into two types - quantitative behavior of "amount of use (time of use, consumption cost)" and qualitative behavior of "perceived satisfaction level (perceived enjoyment, perceived service quality, and perceived price)". As a result of study, in general, as the user quality subjected in this study is stronger, the amount of use and satisfaction level are higher. This study is to observe what type of user qualities leads to the more use, consumption, and satisfaction level of game contents to contribute to the study about the use of conventional digital contents and heavy use.

• 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.

• The Journal of the Korea Contents Association
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• v.18 no.7
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• pp.330-337
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• 2018

Recently, there has been a growing interest in user-centered smart city services. In this study, user behavior analysis was performed as a preliminary study for user - centered smart city service planning. In particular, we will use GIS based location analysis data and video ethonography methodology to derive smart city service direction and needs. In this study, the area of Daejeon Design District selected as the Smart City Test bed was selected as the survey area and the location analysis data of the traffic accident analysis system of the road traffic corporation and the fixed camera We observed user's behavior type and change with image data extracted through the technique. Location analysis data is classified according to the type of accident, and image data is classified into 11 subdivided types of user activities. The problems and specificities observed were analyzed. The user behavior characteristics investigated through this study are meaningful to provide a basis for suggesting user - centered smart city services in the future.

• Journal of Digital Convergence
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• v.10 no.9
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• pp.73-78
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• 2012

The appearance and evolution of cloud service is potentially one of the major advances in information and communication technology. However, it is necessary to identify and understand the various issues of cloud service, both from the perspectives of the providers and the consumers of it. While a lot of studies such as cloud business model, profit model and technology itself are currently taking place in cloud service considering provider's aspects, there are a few researches dealing with cloud service user's aspects. This paper presents the user behavior analysis focused on SaaS users and discusses the development strategy of SaaS service based on the results of user behavior analysis. In order to analyze the user behavior, we surveyed SaaS users divided into two groups such as present and future user groups. Eventually, we proposed the SaaS prospects, development strategy and policy issues based on user behavior analysis.

• Journal of the HCI Society of Korea
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• v.4 no.2
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• pp.1-8
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• 2009

User-centered design aims to develop device naturally without the interference of user' s conscious and unconscious behavior. Accordingly, designers need to understand their user's requirements, observe user behavior and interaction in the real environment. However, existing observations suggested a vast range of analysis system and observation techniques which are often ambiguous to the designers. Therefore, this research is aimed to propose an observation system for collecting data from user's behavior. In order to do so, we define the components and behavior level within the context of driving.