• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.05a
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• pp.342-351
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• 2002

A personalized product recommendation is an enabling mechanism to overcome information overload occurred when shopping in an Internet marketplace. Collaborative filtering has been known to be one of the most successful recommendation methods, but its application to e-commerce has exposed well-known limitations such as sparsity and scalability, which would lead to poor recommendations. This paper suggests a personalized recommendation methodology by which we are able to get further effectiveness and quality of recommendations when applied to an Internet shopping mall. The suggested methodology is based on a variety of data mining techniques such as web usage mining, decision tree induction, association rule mining and the product taxonomy. For the evaluation of the methodology, we implement a recommender system using intelligent agent and data warehousing technologies.

• Proceedings of the Korea Society of Design Studies Conference
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• 2002.05b
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• pp.154-155
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• 2002

• The Journal of Korean Association of Computer Education
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• v.4 no.2
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• pp.71-83
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• 2001

The purpose of this study was to explore the status of development, dissemination, and usage of web courseware for elementary school. Also, this study investigated the problems and improvement strategies. The subjects were 52 researchers from Offices of Education and private companies and 528 teachers and 527 students from elementary schools. Questionnaires were used to collect the data. The study results indicated as follows: First, web courseware are insufficient. It is necessary to provide sufficient budgetary support for development of web courseware. Second, many of web courseware are inconsistent with the curriculum and class environment. To resolve this problem, more teachers should be involved in web courseware development. Third, web courseware usage level was very low because of the lack of information and training. In-service training program should be changed from computer literacy oriented to teaching method with web courseware.

• Knowledge Management Research
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• v.10 no.2
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• pp.85-103
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• 2009

Web 2.0, characterized as openness, sharing, and participation, has enabled Internet users to easily generate a variety of contents, and to share them through Web 2.0 services. Knowledge search service (KSS) is positioning itself as one of typical Web 2.0 services. Yet, few studies have sharpened our understanding of users' knowledge sharing behavior in the KSS environment. In order to address this knowledge void, this paper attempts to explore antecedents of their usage behavior in the KSS environment. Typically, they utilize stored knowledge and share their knowledge simultaneously. Considering this characteristic, our study regards service usage intention and knowledge sharing intention as final dependent variables. This study advances a research model based on Bhattacherjee's expectation-confirmation model, which is expanded by incorporating trust belief. Because of the openness of KSS, trust belief is believed to play a critical role in forming users' service usage intention and knowledge sharing intention. Furthermore, this study examines the difference of the antecedents' effects in terms of users' gender. We collected data from 275 respondents who have experience in using KSS. PLS (partial least squares) was employed for the analysis of the data. Analysis results confirm the important role of user satisfaction and trust belief in the formation of users' service usage intention and knowledge sharing intention. More importantly, trust belief has a more salient effect on knowledge service usage intention than user satisfaction. This study also shows the moderating role of users' gender. Finally, this paper provides managerial guidance on strategic planning aimed at improving users' service usage intention and knowledge sharing intention in the KSS environment.

• Spatial Information Research
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• v.23 no.3
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• pp.45-54
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• 2015

Since the V-World, the Spatial Information Open Platform service, has started in 2012, a lot of people have increased explosively every year with their interest. It is necessary to know the specific service status in order to serve as indicators of the improvement of user's environment and the service to be added in the future based on the user's increasing need. However, there is difficulty to figure out more specific service status, such as the usage of hardware resources for 2D / 3D / Portal services and the actual user usage patterns, because the current system does not have the real-time monitoring system. Therefore, in this paper, through the analysis of the usage of system resources for 2D / 3D / Portal services based on web server log and the usage of hardware resources such as CPU, Memory based on system log, we analyze the usage of service in 2015 and compare with the results of the 2014, to present problems of the current system and the solutions about the problems.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.12
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• pp.4752-4759
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• 2010

Using Technology Acceptance Model and flow theory as our foundation, this paper investigates the interrelationships among social influence, individual cognition, flow, and actual usage in the Web 2.0 environment. According to TAM, users evaluate perceived usefulness(PU) and ease of use(PEU) of information technology(IT) in accepting the innovative IT. Along with users' cognitive evaluation(i.e. PU and PEU), in case of UCC(user-created-contents), which is one of the representative Web 2.0 features, flow also has a significant effect on users' usage. Accordingly, the current study involve cognitive elements such as PU and PEU as well as flow of enjoyable state during using IT in exploring antecedents leading to UCC usage. On one hand, we consider the effect of social influence on users' cognition and flow toward actual usage because the more users creates Web contents, the more long-tail situation prevails on the Internet. Web 2.0 becomes a kind of social phenomena. The empirical results show that social influence affects positively both PU/PEU and flow. Users' cognitive evaluation and flow have positive impacts on users' UCC usage.

• Journal of Intelligence and Information Systems
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• v.9 no.3
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• pp.177-191
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• 2003

Recommender systems are a personalized information filtering technology to help customers find the products they would like to purchase. Collaborative filtering is the most successful recommendation technology. Web usage mining and clustering analysis are widely used in the recommendation field. In this paper, we propose several hybrid collaborative filtering-based recommender procedures to address the effect of web usage mining and cluster analysis. Through the experiment with real e-commerce data, it is found that collaborative filtering using web log data can perform recommendation tasks effectively, but using cluster analysis can perform efficiently.

• Korean Management Science Review
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• v.21 no.1
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• pp.1-17
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• 2004

A separate and distinct interaction with both the actual e-vendor and with its IT web site interface is at the heart of online shopping. Previous research has established, accordingly, that online purchase intention is the product of customer assessments of IT itself, specifically its perceived usefulness and ease-of-use(TAM). Since perceived usefulness and perceived ease of use are such a fundamental driver of usage intentions, it is important to understand the determinants of this construct and how their influence changes over the voluntariness towards the usage intention. The reason for voluntariness as a moderating variable is that it had the serious effect to the motivating in the making willingness of the internet shopping-mall usage. A better understanding of the determinants of perceived usefulness and perceived ease of use to the usage intention would enable us to design web site interventions that would increase user acceptance and usage of internet shopping-mall. Therefore, the goal of the present research is to extend TAM to include additional key determinants of TAM and to understand how the effects of these determinants change with the voluntariness of the usage intention of the internet shopping-mall.

• Korea Journal of Hospital Management
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• v.16 no.3
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• pp.41-56
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• 2011

The research was to investigate the effect of quality cognition of the web site of the facility and relationship commitment on customer loyalty. The respondents were 190 patients and caregivers. Data were collected from March 1st to 31st, 2010 at C university hospital in G city. The effect of facility web site of quality cognition and relationship commitment on customer loyalty showed 43.9%(F=35.806) in model 1, 58.4%(F=51.113) in model 2, and 58.7%(F=28.185) in model 3. Also, medical information & usage, aesthetics was significance in model 1, medical information & usage, relationship commitment in model 2. In relationship between web site quality cognition and customer loyalty, moderate effect of relationship commitment were not considerable in model 3. As a result, customer loyalty is the leading fact for quality cognition of the web site more than relationship commitment. Therefore, customer loyalty leaves its possibility of increment when facility web site is designated depending on medical information and aesthetics.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.271-279
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• 2001

Sequential pattern discovery is one of main interests in web usage mining. the technique of sequential pattern discovery attempts to find inter-session patterns such that the presence of a set of items is followed by another item in a time-ordered set of server sessions. In this paper, a tree-based sequential pattern finding method is proposed in order to discover navigation patterns in server sessions. At each learning process, the suggested method learns about the navigation patterns per server session and summarized into the modified Rymon's tree.