• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.613-614
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• 2008

A content recommendation according to users preferences comes up in the Internet application due to contents overwhelming. This paper newly proposes a method to predict contents preference using tags in conjunction with Content-Based Filtering. By implementing this method, this paper cleans up the contents sparsity problem in Content-Based Filtering, and shows the outstanding improvements.

• Asia pacific journal of information systems
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• v.12 no.3
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• pp.71-88
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• 2002

In this paper, intelligent marketing and merchandising methods utilizing data mining and Web mining techniques are proposed for online retailers to survive and succeed in gaining competitive advantage in a highly competitive environment. The first part of this paper explains the procedures of one-to-one marketing based on customer relationship management(CRM) techniques and personalized recommendation lists generation. The second part illustrates Web merchandising methods utilizing data mining techniques, such as association and sequential pattern mining. We expect that our Web marketing and merchandising methods will both provide a currently operating Internet shopping mall with more selling opportunities and give more useful product information to customers.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.577-582
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• 2013

In this paper, the state-of-the-art IVEF Service based on e-Navigation System was represented. The unification of the data exchange format among maritime-related systems is one of vital user-needs of e-Navigation, advantageous in bringing maritime safety and security. This paper propose the method to exchange marine information in IVEF, as recommended by the IALA, between VTS centers and Korea's GICOMS as well as the government-related agencies. To achieve this, a system data flow was designed which it acts as client and server. It enables the sending and receiving of Radar and CCTV images in accordance with the IVEF recommendation document of IALA.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.10 no.6
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• pp.910-916
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• 1999

This paper presents the effective improvement of the thermal runaway phenomenon in high power SSPA when the RF input signal is not provided. The total gate resistors are optimized by the experiments and deducing the variation of velocity and currents of thermal runaway, which is based on manufacturer's recommendation. Especially, it is solved the complex thermal runaway that related gate resistors with the gate voltage variable circuit. The result of this paper is able to apply for improving the thermal runaway in existence of high power SSPA for WLL, cellular system and PCS repeater.

• Journal of Information Processing Systems
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• v.15 no.4
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• pp.931-956
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• 2019

Documents contain information that can be used for various applications, such as question answering (QA) system, information retrieval (IR) system, and recommendation system. To use the information, it is necessary to develop a method of extracting such information from the documents written in a form of natural language. There are several kinds of the information (e.g., temporal information, spatial information, semantic role information), where different kinds of information will be extracted with different methods. In this paper, the existing studies about the methods of extracting the temporal information are reported and several related issues are discussed. The issues are about the task boundary of the temporal information extraction, the history of the annotation languages and shared tasks, the research issues, the applications using the temporal information, and evaluation metrics. Although the history of the tasks of temporal information extraction is not long, there have been many studies that tried various methods. This paper gives which approach is known to be the better way of extracting a particular part of the temporal information, and also provides a future research direction.

• Journal of Distribution Science
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• v.14 no.8
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• pp.5-8
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• 2016

Purpose - With its considerable water resources, Lao People's Democratic Republic, hereafter Lao PDR, is considered to become the "battery" of the Southeast Asia region in the next 20 years. This paper explores the investment opportunity in the hydroelectricity development project in the Lao PDR. Research design, data, and methodology - Three significant investment factors including cultural factor, political factors, and economic factors are being literally analyzed. In fulfilling the purpose of this analysis, Num Theun 2 Power Company or NTPC, a current largest hydropower project in the country, is selected for an example of a mega investment project model in the country. Results - NTPC's investment plan, budgets, and current revenue and rate of return are briefly discussed throughout the paper. In addition, this paper also briefly compares and contrasts of the investment in the Lao PDR and investment in its neighboring Singapore who is considered one of the leading developed economies in the region. Conclusions - A recommendation is being proposed on the last section of this paper in the areas that Lao PDR may consider adopting in order to make its investment environment becomes more attractive to foreign investors.

• The Journal of Society for e-Business Studies
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• v.16 no.3
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• pp.191-209
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• 2011

In a buyer-seller transaction process, 'value for money,' a measure of quality-price-ratio, is one of the most important criteria for buyers' purchasing decisions. The purpose of this paper is to suggest a method which helps online shoppers choose the best of several sellers offering homogeneous goods. We suggest FDH (free disposal hull) model, an applied model of data envelopment analysis (DEA), for online buyer-seller transactions and verify it with the data from an Internet comparison shopping site. For this purpose, we analyze consumer choice behaviors by examining how consumers respond to different sale conditions such as price, brand, or delivery time. Then, we implement a seller recommendation system to support buyers' purchasing decisions. We expect our FDH model to provide valuable information for rational buyers who want to pay the least price for high quality products/services and to be used in implementing automated evaluation processes in micro transactions. Moreover, we expect that our results can be utilized for sellers' benchmarking strategies which help sellers be more competitive by showing them how to attract buyers.

• Journal of Satellite, Information and Communications
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• v.1 no.2
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• pp.8-15
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• 2006

Under Resolution 122 (Rev. WRC-03), ITU-R is invited to study, as a matter of urgency, power limitations applicable for HAPS ground stations to facilitate sharing with space station receivers in the bands 47.2-47.5 GHz and 47.9-48.2 GHz. However, there have been no studies on this issue. Recommendation ITU-R SF.1481-1 which was developed during past study period, provides methodology and system characteristics for analyzing the sharing feasibility between systems in the FS using HAPS and systems in the FSS. System characteristics for a typical HAPS in the bands above are also given in Recommendation ITU-R F.1500. This paper provides the results on power limitations applicable for HAPS ground stations in accordance with Resolution 122 (Rev. WRC-03). As already shown in ITU-R Recommendation the results show that a sufficient separation distance is required for sharing between HAPS ground stations and FSS satellite systems. We obtain some examples of the sharing conditions considering reducing the power level of HAPS ground stations and using the antenna beam pattern with the low sidelobe to decrease the interference level affecting FSS satellite receiver.

• Journal of the Korea Society for Simulation
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• v.15 no.3
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• pp.23-30
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• 2006

A recommender system for E-commerce site receives information from customers about which products they are interested in, and recommends products that are likely to fit their needs. In this paper, we investigate several methods for large-scale product purchase data for the purpose of producing useful recommendations to customers. We apply the traditional data mining techniques of cluster analysis and collaborative filtering(CF), and CF with reduction of product-dimensionality by use of latent semantic indexing(LSI). If reduced product-dimensionality obtained from LSI shows a similar latent trend of customers for buying products to that based on original customer-product purchase data, we expect less computational effort for obtaining the nearest-neighbor for target customer may improve the efficiency of recommendation performance. From simulation experiments on synthetic customer-product purchase data, CF-based method with reduction of product-dimensionality presents a better performance than the traditional CF methods with respect to the recall, precision and F1 measure. In general, the recommendation quality increases as the size of the neighborhood increases. However, our simulation results shows that, after a certain point, the improvement gain diminish. Also we find, as a number of products of recommendation increases, the precision becomes worse, but the improvement gain of recall is relatively small after a certain point. We consider these informations may be useful in applying recommender system.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.33-46
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• 2011

Since an e-mail has been an important mean of communication and information sharing, there have been much effort to classify e-mails efficiently by their contents. An e-mail has various forms in length and style, and words used in an e-mail are usually irregular. In addition, the criteria of an e-mail classification are subjective. As a result, it is quite difficult for the conventional text classification technique to be adapted to an e-mail classification efficiently. An e-mail classification technique in a commercial e-mail program uses a simple text filtering technique in an e-mail client. In the previous studies on automatic classification of an e-mail, the Naive Bayesian technique based on the probability has been used to improve the classification accuracy, and most of them are on an e-mail in English. This paper proposes the personalized recommendation technique of an email in Korean using a data mining technique of frequent patterns. The proposed technique consists of two phases such as the pre-processing of e-mails in an e-mail folder and the generating a profile for the e-mail folder. The generated profile is used for an e-mail to be classified into the most appropriate e-mail folder by the subjective criteria. The e-mail classification system is also implemented, which adapts the proposed technique.