• The KIPS Transactions:PartA
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• v.10A no.2
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• pp.131-136
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• 2003

Comparison criteria and a selection model for concurrency control algorithms has been presented in this article. In addition, a comparison analysis has been performed with the developed comparison model. The result of the analysis can be utilized to select the best fitting concurrency control algorithm to the user's existing system environment.

• Proceedings of the KSR Conference
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• 2005.11a
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• pp.488-493
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• 2005

Railload line design of the railroad construction project should be planed considering the variety of quantitative and qualitative factors, and needs to be selected the optimum altinative weighing from VE/LCC analysis of the planned design. The purpose of this research is for showing selecting plan of the optimum railload line and railway bridge applying VE/LCC analysis in selecting the optimum altinative of railroad construction based on quantitative and qualitative factors, such as initial construction cost, maintenance cost, owner and user's requirements. In this research showed the application plan by each stage using data analysis, function analysis, and alternative evaluation of VE/LCC analysis with AHP and LCC analysis program for the selection. This research is proved the rationality and application of the course of selecting the optimum alternative through case application

• Journal of Broadcast Engineering
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• v.7 no.2
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• pp.88-95
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• 2002

According to an evolution of digital broadcasting, it is possible that terrestrial and satellite broadcasting media provide multi-channel services. CATV and satellite media have been also extended to hundreds of channels. As the result of channel expanding, viewers came to select lots of channels. But it is difficult that they select the favorite channel among hundreds of channels. In this paper, we propose an efficient automatic method to recommend channels and programs on a viewer's preference in a multi-channel broadcasting receiver like a Set ToP Box(STB). The proposed algorithm selects channels based on the following method. It makes and saves user history data by using MPEG-7 MDS based on the program information a viewer had watched. It recommends programs similar to a viewer's preference based on user history data. It selects the channel in the recommended genre based on the viewer's channel preference. The experimental result shows that the proposed scheme is efficient to select the user preference channel.

• The Journal of Information Systems
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• v.17 no.2
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• pp.137-154
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• 2008

Customer Relationship Management (CRM) is indispensable for companies in recent business environment, in which the customers are recognized as more valuable asset to increase the earning power of enterprise. For gaining competitive advantage, most companies want to maintain existing customer relationships and generate more profits with customers through long-term relationships. In this study, we developed the models which are designed to select CRM systems in financial institution, which is one of competitive sectors and undergoes rapid changes due to M&A(Merger and acquisition), innovation and reengineering in Korea. The selection model of CRM systems for financial institution was developed utilizing the Analytic Hierarchy Process (AHP) and the expert's knowledge were built up of three groups; researcher group, developer group, and user group. We found that there are significant deferences for the weights of criteria in our selection model according to the kind of experts. This study provides helpful guidance on how to assign appropriate weights to each criteria in selection models when financial institution introduce the CRM systems.

• Journal of Information Technology Applications and Management
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• v.24 no.1
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• pp.33-43
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• 2017

The content curation service through big data analysis is receiving great attention in various content fields, such as film, game, music, and book. This service recommends personalized contents to the corresponding user based on user's preferences. The existing book curation systems recommended books to users by using bibliographic citation, user profile or user log data. However, these systems are difficult to recommend books related to character names or spatio-temporal information in text contents. Therefore, in this paper, we suggest a personalized book curation system based on integrated mining of a book. The proposed system consists of mining system, recommendation system, and visualization system. The mining system analyzes book text, user information or profile, and SNS data. The recommendation system recommends personalized books for users based on the analysed data in the mining system. This system can recommend related books using based on book keywords even if there is no user information like new customer. The visualization system visualizes book bibliographic information, mining data such as keyword, characters, character relations, and book recommendation results. In addition, this paper also includes the design and implementation of the proposed mining and recommendation module in the system. The proposed system is expected to broaden users' selection of books and encourage balanced consumption of book contents.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.26 no.4
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• pp.105-121
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• 2015

PDA model is new collection development method not only corresponding user's demand, but also expensing acquisition budget effectively. In the PDA model, when the trigger that indicates user's demand reaches up to treshold, e-book is automatically purchased without librarian's interrogation. This study examines concept, basic principles, and current condition of operation about PDA and finds a way that could applicate to Korean university library foreign E-book consortium. Current model of university library e-book acquisition pursuit reduction of budget and utility value, but the selected collection is not based on user's demand. Therefore, it could be considerable to apply PDA or evidence based purchase model to foreign e-book acquisition consortium.

• Information Systems Review
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• v.14 no.3
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• pp.115-129
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• 2012

A matchmaking system is a type of recommender systems that provides a set of dating partners suitable for the user by online. Many matchmaking systems, which are widely used these days, require users to specify their preferences with regards to ideal dating partners based on criteria such as age, job and salary. However, some users are not aware of their exact preferences, or are reluctant to reveal this information even if they do know. Also, users' selection standards are not fixed and can change according to circumstances. This paper suggests a new matchmaking system called Decision Tree based Matchmaking System (DTMS) that automatically adjusts the stated standards of a user by analyzing the characteristics of the people the user chose to contact. AMMS provides recommendations for new users on the basis of their explicit preferences. However, as a user's behavioral records are accumulated, it begins to analyze their hidden implicit preferences using a decision tree technique. Subsequently, DTMS reflects these implicit preferences in proportion to their predictive accuracy. The DTMS is regularly updated when a user's data size increases by a set amount. This paper suggests an architecture for the DTMS and presents the results of the implementation of a prototype.

• Journal of the Korea Society of Computer and Information
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• v.13 no.1
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• pp.1-10
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• 2008

In order to high-performance data Processing, effective resource selection is needed since grid resources are composed of heterogeneous networks and OS systems in the grid environment. In this paper. we classify grid resources with data properties and user requirements for resource selection using a decision tree method. Our resource selection method can provide suitable resource selection methodology using classification with a decision tree to grid users. This paper evaluates our grid system performance with throughput. utilization, job loss, and average of turn-around time and shows experiment results of our resource selection model in comparison with those of existing resource selection models such as Condor-G and Nimrod-G. These experiment results showed that our resource selection model provides a vision of efficient grid resource selection methodology.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.632-634
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• 2012

In order for the connection to the wireless network from the list of priorities of the wireless AP to AP profile automatic connection by selecting the preferred method to register a profile, which is determined at the time of the change, the user does not respond to the demands of the part. In this study, the frequency of the user's access in accordance with the wireless AP, and by creating a profile, the user needs to meet with regard to network access adaptive research.

• Journal of Software Assessment and Valuation
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• v.15 no.1
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• pp.123-131
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• 2019

The Internet of Things (IoT) environment must be able to meet the needs of users by providing access to various services that can be used to develop diverse user applications. However, QoS issues arise due to the characteristics of the IoT environment, such as numerous heterogeneous devices and potential resource constraints. In this paper, we propose a QoS prediction method that reflects trust between users in SOA based IoT. In order to increase the accuracy of QoS prediction, we analyze the trust and distrust relations between users and identify similarities among users and predict QoS based on them. The centrality is calculated to enhance trust relationships. Experimental results show that QoS prediction can be improved.