• The KIPS Transactions:PartB
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• v.19B no.4
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• pp.237-242
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• 2012

Web information service needs a document classification system for efficient management and conveniently searches. Existing document classification systems have a problem of low accuracy in classification, if a few number of feature words is selected in documents or if the number of documents that belong to a specific category is excessively large. To solve this problem, we propose a document classification system using 'Modified ECCD' feature selection method and 'Category Weight for each Document'. Experimental results show that the 'Modified ECCD' feature selection method has higher accuracy in classification than ${\chi}^2$ and the ECCD method. Moreover, combining the 'Category Weight for each Document' feature value and 'Modified ECCD' feature selection method results better accuracy in classification.

• Journal of KIISE:Databases
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• v.41 no.4
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• pp.199-208
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• 2014

In this paper, we represent a system of identification and feature search for scanned comics in consideration of their content characteristics. For creating the feature of the scanned comics, we utilize a method of hierarchical symmetry fingerprinting. Proposed identification and search system is designed to give online service provider, such as Webhard, an immediate identification result under conditions of huge volume of the scanned comics. In simulation part, we analyze the robustness of the identification of the fingerprint to image modification such as rotation and translation. Also, we represent a structure of database for fast matching in feature point database, and compare search performance between other existing searching methods such as full-search and most significant feature search.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2399-2413
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• 2021

A recommendation system is an information filter tool, which uses the ratings and reviews of users to generate a personalized recommendation service for users. However, the cold-start problem of users and items is still a major research hotspot on service recommendations. To address this challenge, this paper proposes a high-efficient hybrid recommendation system based on Fuzzy C-Means (FCM) clustering and supervised learning models. The proposed recommendation method includes two aspects: on the one hand, FCM clustering technique has been applied to the item-based collaborative filtering framework to solve the cold start problem; on the other hand, the content information is integrated into the collaborative filtering. The algorithm constructs the user and item membership degree feature vector, and adopts the data representation form of the scoring matrix to the supervised learning algorithm, as well as by combining the subjective membership degree feature vector and the objective membership degree feature vector in a linear combination, the prediction accuracy is significantly improved on the public datasets with different sparsity. The efficiency of the proposed system is illustrated by conducting several experiments on MovieLens dataset.

• Journal of the Korea Society of Computer and Information
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• v.15 no.11
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• pp.91-99
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• 2010

Recently, recognizing user resource for personalized service has been needed in digital content service fields. Especially, to analyze user taste, recommend music and service music related information need recognition of user music file in case of online music service. Music related information service is offered through recognizing user music based on tag information. Recognition error has grown by weak points like changing and removing of tag information. Techniques of content based user music recognition with music signal itself are researched for solving upper problems. In this paper, we propose user music recognition on the internet by extracted feature from music signal. Features are extracted after suitable preprocessing for structure of content based user music recognition. Recognizing on music server consist of feature form are progressed with extracted feature. Through this, user music can be recognized independently of tag data. 600 music was collected and converted to each 5 music qualities for proving of proposed recognition. Converted 3000 experiment music on this method is used for recognition experiment on music server including 300,000 music. Average of recognition ratio was 85%. Weak points of tag based music recognition were overcome through proposed content based music recognition. Recognition performance of proposed method show a possibility that can be adapt to online music service in practice.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.555-557
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• 2003

Location-based services allow consumers to receive services based on their geographic location data. For example, businesses can provide information to find traffic facility, public restaurant, a hospital, and a station based on the consumer’s location at a particular moment. Also, they wish to grasp a accurate location based service in mobile device or PDA. So, this paper shows that presentation service offers a base-map to be overlaid OpenLS (Open Location Services)’s directory service, route determination service, geocode and reverse-geocode service. The presentation service is the portrayal of a map and portrayal of feature as map overlays.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.4
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• pp.60-66
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• 2016

Compound logistics is a service aimed to enhance logistics efficiency by supporting that shippers and consigners jointly use logistics facilities. Many of these services have taken place both domestically and internationally, but the joint logistics services for e-commerce have not been spread yet, since the number of the parcels that the consigners transact business is usually small. As one of meaningful ways to improve utilization of compound logistics, we propose a brokerage service for shipper and consigners based on the hybrid recommendation system using very well-known classification and clustering methods. The existing recommendation system has drawn a relatively low satisfaction as it brought about one-to-one matches between consignors and logistics vendors in that such matching constrains choice range of the users to one-to-one matching each other. However, the implemented hybrid recommendation system based brokerage agent service system can provide multiple choice options to mutual users with descending ranks, which is a result of the recommendation considering transaction preferences of the users. In addition, we applied feature selection methods in order to avoid inducing a meaningless large size recommendation model and reduce a simple model. Finally, we implemented the hybrid recommendation system based brokerage agent service system that shippers and consigners can join, which is the system having capability previously described functions such as feature selection and recommendation. As a result, it turns out that the proposed hybrid recommendation based brokerage service system showed the enhanced efficiency with respect to logistics management, compared to the existing one by reporting two round simulation results.

• Journal of Digital Contents Society
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• v.19 no.7
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• pp.1313-1322
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• 2018

This study has tested by positive analysis to investigate use intention of self service shop offered by franchisee. The independent variable of self service shop consisted of technology based self service and feature of shop largely. Convenience of technology based self service, speed, functionality of shop feature, suitability, and cost of self service shop had been selected. As parameter, expectation confirmation and satisfaction by using Expectation confirmation theory had been selected and a dependent variable had been selected use intention lastly. The study conducted a survey of self service shop customers and 181's answers out of them had been used. According to the analysis result, convenience, speed, functionality, and suitability had a positive effect on expectation and convenience and suitability variables only had positive effect on satisfaction. The cost did not have an effect on use intention and expectation confirmation and satisfaction had a positive effect on use intention lastly.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.6
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• pp.1374-1379
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• 2015

Malicious network attacks such as DDoS has no clear measures, the damage is also enormous. In particular, in addition to a network failure, such as leakage of personal information and damage of the communication charge in the case of zombie smartphone is infected, is expected damages of various users. In this study, we extract the zombie smartphone's phenomena and features that appear while the zombie service is running and introduce a corresponding technique to prevent zombie smartphone.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10b
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• pp.22-24
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• 2003

최근 웹 확산에 따른 일반인들의 인터넷 이용이 급증하였고 이에 따른 정보 기술도 빠르게 변화하고 있다. GIS 분야에서도 시대의 흐름에 맞춰 공간 데이타를 웹상에서 제공하는 웹 GIS 분야가 등장하게 되었다. 그러나, 상호이질적인 공간 데이타를 웹 기반 분산 환경에서 서비스하기 위해 표준 인터페이스와 각각의 웹 서비스 모델을 정의한 통합 시스템이 요구되고 있다. OGC에서는 기존 OPenGIS의 상호운용성을 웹 환경에서 지원하고, 또한 피쳐 인스턴스 단위의 지리정보를 접근하기 위해 새로운 웹 피쳐 서비스 구현 명세를 제안하였다. 웹 피쳐 서비스 구현 명세에서는 클라이언트로부터 HTTP를 통하여 요청된 공간.비공간 질의를 처리하기 위한 URL 컴포넌트를 정의하고 있다. 이 컴포넌트는 클라이언트 질의를 수행하여 피쳐 인스턴스 단위로 데이타를 검색 및 조작하고, 검색된 데이타는 GML로 정의하여 클라이언트로 제공한다. 본 논문에서는 OGC가 제안한 XML 기반의 표준 공간 데이타 포맷인 GML과 웹 피쳐 서비스 인터페이스를 이용해 분산된 지리정보 데이타를 웹 브라우저를 통하여 서비스할 수 있는 웹 피쳐 서비스 시스템을 설계 및 구현하였다.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.2
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• pp.153-162
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• 2006

Customer satisfaction is an ever-growing concern of management throughout the world. To find the way to increase customer satisfaction, we must understand customer requirements. Kano distinguishes between three types of product requirements (must-be, one-dimensional, attractive requirement) which influence customer satisfaction in different ways when met. In this paper, potential customer satisfaction improvement (PCSI) index was developed using Kano model and CS coefficient. Timko has developed customer satisfaction (CS) coefficient based on Kano model. The PCSI index represents how much a service feature can increase the degree of customer satisfaction when the service feature is fully fulfilled. In order to explain the meaning of PCSI index, a case syudy of a Family Restaurant is done. It is also discussed how to use the index strategically.