• Journal of the Ergonomics Society of Korea
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• v.33 no.3
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• pp.175-189
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• 2014

Objective: The goal of this research is to develop new user behavior model using user motion analysis with microscopic perspective for attracting user's participation in interactive space. Background: The interactive space is 'human's place', which is made up of complex elements of digital virtual space and traditional analog and physical environment based on human-computer interaction system. Human behavior has changed in it at the same time. If the user couldn't make participation in interaction, the purpose of the system is not met, which reduces its effect. Therefore, we need to focus on interactive space that is potential future direction from a new point of view. Method: For this research, we would discuss and study fields of interactive space; (1) finding definition of interactive space and studying background of theory about it. (2) providing base of user behavior model with study of user's context that is to be user information and motion. (3) examining user motion, classify basic motion type and making user participation behavior model in phases. Results: Through this process, user's basic twenty motions which are systematized are taken as a standard for analysis of interaction process and participation in interactive space. Then, 'NK-$I^5$ (I Five)' model is developed for user participation types in interactive space. There are five phases of user participation behavior: Imperception, Interest, Involvement, Immersion, and Influence. In this analysis, three indicators which are time, motion types, and user relationship are found to be related to participation. Conclusion: The capabilities and limitation of this research is discussed to attract user participation. This paper focuses especially on contribution of design to lead user's participation in interactive system and expectation to help adapt to user centered design of various interactive space with new aspect of user behavior research. Application: The results of the 'NK-$I^5$ (I Five)' model might help to realize successful interactive space based on user centered design.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.5
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• pp.1963-1978
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• 2015

With the advancement of mobile web environments, identification and analysis of the user behavior play a significant role and remains a challenging task to implement with variations observed in the model. This paper presents an efficient method for mining optimized user behavior prediction model using genetic algorithm on mobile web structure. The framework of optimized user behavior prediction model integrates the temporary and permanent register information and is stored immediately in the form of integrated logs which have higher precision and minimize the time for determining user behavior. Then by applying the temporal characteristics, suitable time interval table is obtained by segmenting the logs. The suitable time interval table that split the huge data logs is obtained using genetic algorithm. Existing cluster based temporal mobile sequential arrangement provide efficiency without bringing down the accuracy but compromise precision during the prediction of user behavior. To efficiently discover the mobile users' behavior, prediction model is associated with region and requested services, a method called optimized user behavior Prediction Model using Genetic Algorithm (PM-GA) on mobile web structure is introduced. This paper also provides a technique called MAA during the increase in the number of models related to the region and requested services are observed. Based on our analysis, we content that PM-GA provides improved performance in terms of precision, number of mobile models generated, execution time and increasing the prediction accuracy. Experiments are conducted with different parameter on real dataset in mobile web environment. Analytical and empirical result offers an efficient and effective mining and prediction of user behavior prediction model on mobile web structure.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3972-3985
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• 2016

Organizations have been implementing mobile applications that actually connect to their backend enterprise applications (e.g. ERP, SCM, etc.) in order to increase the enterprise mobility. However, most of the organizations are still struggling to fully satisfy their mobile application users with the enterprise mobility. Even though it has been regarded as the right direction that the traditional enterprise system should move on, the studies on the success model for mobile enterprise applications in user's acceptance perspective can hardly be found. Thus, this study focused not only to redefine the success of the mobile enterprise application in user's acceptance persepective, but also to find the impacts of the factors on user's usage behavior of the mobile enterprise applications. In order to achieve this, we adopted the Technology Acceptance Model 2 (TAM2) as a model to figure out the user's behavior on mobile applications. Among various mobile enterprise applications, this study chose mobile ERP since it is the most representing enterprise applications that many organizations have implemented in their backend. This study found that not all the constructs defined by Davis in TAM2 have a significant influence on user's behavior of the mobile-ERP applications. However, it is also found that most social influence processes of TAM2 influence user's perception of the degree of interaction by mobile-ERP applications.

• 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 Information Science Theory and Practice
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• v.8 no.3
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• pp.30-46
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• 2020

This research aimed (1) to study and analyze the ability of current information retrieval (IR) systems based on views of information behavior (IB), and (2) to propose a conceptual framework for an IB model based on the collaboration between the system and user, with the intent of developing an IR system that can apply intelligent techniques to enhance system efficiency. The methods in this study consisted of (1) document analysis which included studying the characteristics and efficiencies of the current IR systems and studying the IB models in the digital environment, and (2) implementation of the Delphi technique through an indepth interview method with experts. The research results were presented in three main parts. First, the IB model was categorized into eight stages, different from traditional IB, in the digital environment, which can correspond to all behaviors and be applied to with an IR system. Second, insufficient functions and log file storage hinder the system from effectively understanding and accommodating user behavior in the digital environment. Last, the proposed conceptual framework illustrated that there are stages that can add intelligent techniques to the IR system based on the collaboration perspective between the user and system to boost the users' cognitive ability and make the IR system more user-friendly. Importantly, the conceptual framework for the IB model based on the collaboration perspective between the user and system for IR assisted the ability of information systems to learn, recognize, and comprehend human IB according to individual characteristics, leading to enhancement of interaction between the system and users.

• Journal of the Korea Society of Computer and Information
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• v.21 no.3
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• pp.97-104
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• 2016

In this paper, we propose spatial information based simulator for user experience optimization and minimize real space complexity. We focus on developing simulator how to design virtual space model and to implement virtual character using real space data. Especially, we use expanded events-driven inference model for SVM based on machine learning. Our simulator is capable of feature selection by k-fold cross validation method for optimization of data learning. This strategy efficiently throughput of executing inference of user behavior feature by virtual space model. Thus, we aim to develop the user experience optimization system for people to facilitate mapping as the first step toward to daily life data inference. Methodologically, we focus on user behavior and space modeling for implement virtual space.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.177-187
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• 2024

177-Existing music recommendation systems do not sufficiently consider the discrepancy between the intended emotions conveyed by song lyrics and the actual emotions felt by users. In this study, we generate topic vectors for lyrics and user comments using the LDA model, and construct a user preference model by combining user behavior trajectories reflecting time decay effects and playback frequency, along with statistical characteristics. Empirical analysis shows that our proposed model recommends music with higher accuracy compared to existing models that rely solely on lyrics. This research presents a novel methodology for improving personalized music recommendation systems by integrating emotion recognition and user behavior analysis.

• Proceedings of the Korea Society of Design Studies Conference
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• 2002.11b
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• pp.56-57
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• 2002

• Journal of Multimedia Information System
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• v.6 no.4
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• pp.179-184
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• 2019

This paper introduces a study for procedurally generating the behavior of objects in a virtual environment at runtime. This study was initiated to enable the behavioral model of objects in virtual reality applications to evolve in response to user behavior at runtime. Our approach is to describe the behavior of an object as a behavior tree, and to make a node of the behavior tree change to another type if a certain condition is satisfied. We defined four types of node changes: "parameterized", "probabilistic", "alternate", and "variant". We experimented with a virtual environment that includes a variety of simple procedural elements to explore the possibilities of our approach. As a result of the implementation, if an optimization algorithm that can select and apply the optimized procedural elements in response to the user's behavior is complemented, it is confirmed that more intelligent objects and agents can be implemented in virtual reality applications.

• Journal of Korea Multimedia Society
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• v.5 no.6
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• pp.730-744
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• 2002

A Web-Based Information System(WBIS), a typical structure of recently information systems, should be dynamically restructured in order to satisfy user's need and make a profit. Thus, we should analyze and modelize the navigational structure of WBIS and utilize it by modeling the navigational structure of behavior of user through log-file as system restructuring. In this paper, we propose the modeling method for navigational structure and user behavior to restructure WBIS including shopping mall. Also, we suggest the structural model, state transition model, Petri net model and analysis method and analyze and implement modeling algorithm for user behavior to analyze log-file of it. Then, we propose some restructuring heuristic and apply the methods to the example of WBIS.