• Proceedings of the Korean Information Science Society Conference
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• 2001.10a
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• pp.298-300
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• 2001

최근 들어 기업이나 관공서, 기관 등에서 상호간에 정보를 서로 교환하거나 사용자에게 게시할 때, 대부분 웹을 통해 브라우저에서 볼 수 있도록 HTML(HyperText Markup Language)형태로 제작하게 된다. 그러나 HTML로 제작된 웹 페이지는 구조적인 정보나 다양한 정보를 표시할 수 없다는 문제점이 있으며, 빠르게 변하는 정보인 경우 상세한 정보 표현 면에서 취약하다는 단점이 있다. XML(eXtensible Markup Language)은 이러한 문제점을 해결할 수 있는 마크업(markup) 언어로써 차세대 데이터 교환의 표준으로 채택하고 있다. 한편, XML이 HTML보다 더 나은 구조와 기능을 제공하고 있으나 XML 자체만으로는 XML이 가지는 여러 가지 장점들을 충분히 활용하기 어렵기 때문에 스크립트 언어의 사용이나 애플리케이션의 제작이 필수적이다. 본 논문에서는 효율적인 정보의 교환과 공유를 위해 XForm과 XML Query를 사용하여 정보를 데이터베이스에 저장하고 XML 형태로 추출, 교환할 수 있으며, 서버(server)와 클라이언트(client) 사이에서의 정보 교류뿐만 아니라 유사한 컨텐츠를 제공하는 여러 서버들간의 정보 공유를 지원하는 정보 처리 시스템을 제안한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.5
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• pp.609-617
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• 2011

This paper proposes a personalized food recommendation system using user profiles auto-generated from Twitter. The user profiles are generated by extracting nouns from Twitter, and calculating emotional scores according to whether each noun is collocated with emotion words. Representative noun information for each food is constructed by analyzing web pages relevant to foods. Appropriate foods for users can be recommended by calculating similarities among the extracted resources. The proposed system has an advantage in that it can always recommend foods even if a user is a newcomer.

• The KIPS Transactions:PartD
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• v.15D no.4
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• pp.485-494
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• 2008

Huge amounts of various web items such as keywords, images, and web pages are being made widely available on the Web. The popularities of such web items continuously change over time, and mining temporal patterns in popularities of web items is an important problem that is useful for several web applications. For example, the temporal patterns in popularities of search keywords help web search enterprises predict future popular keywords, enabling them to make price decisions when marketing search keywords to advertisers. However, presence of millions of web items makes it difficult to scale up previous techniques for this problem. This paper proposes an efficient method for mining temporal patterns in popularities of web items. We treat the popularities of web items as time-series, and propose gapmeasure to quantify the similarity between the popularities of two web items. To reduce the computation overhead for this measure, an efficient method using the Fast Fourier Transform (FFT) is presented. We assume that the popularities of web items are not necessarily following any probabilistic distribution or periodic. For finding clusters of web items with similar popularity trends, we propose to use a density-based clustering algorithm based on the gap measure. Our experiments using the popularity trends of search keywords obtained from the Google Trends web site illustrate the scalability and usefulness of the proposed approach in real-world applications.

• Journal of KIISE:Software and Applications
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• v.26 no.8
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• pp.946-954
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• 1999

웹의 등장으로 전자 업무 처리는 급격한 성장을 보여왔다. 많은 업계에서는 업무 처리에 있어 핵심이 되는 트랜잭션을 웹에서 처리하기 위한 시스템 개발에 많은 노력을 기울여왔다. 그러나 대부분의 웹 트랜잭션 연구는 주로 CGI 방식의 트랜잭션 처리 성능의 한계를 극복하거나, 여러 HTTP 요청간의 상태 유지 방법 또는 시스템의 확장성 등에 대해 연구가 집중된 반면, 부적합한 웹 환경으로 유발되는 시스템의 일관성 손실에 대해서는 많은 관심을 받지 못했다.본 논문에서는 웹 상에서 신뢰성 있는 트랜잭션을 처리하는 경우 발생되는 세 가지 문제점을 지적하고, 이를 막기 위해 웹 트랜잭션 처리 시스템인 WebTP에서 제공하는 해결책을 제안한다. 제안한 해결책은 쿠키 로깅, 웹 페이지 로깅, 그리고 일방적으로 철회된 트랜잭션의 상태를 유지하는 기법을 근간으로 한다. 또한 제안된 방법은 유사 구조의 타 웹 트랜잭션 처리 시스템에서도 적용 가능하다.Abstract Electronic business processing has drastically grown since the advent of the World Wide Web. As transaction processing is at heart of business processing, many companies have been interested in transaction processing on the Web. However, little attention has been paid to supporting consistent transaction processing on the Web, while most of the work has been focused on performance enhancement, processing multiple HTTP requests in a single context, and scalability.This paper identifies three problems in consistent transaction processing on the Web, and proposes corresponding solutions for each problem. The results are implemented in the Web transaction processing system WebTP. These solutions are based on cookie logging, Web page logging and keeping information for unilaterally aborted transactions. The solutions proposed in this paper also can be applied to other Web transaction processing system of similar architecture.

• Journal of Digital Contents Society
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• v.16 no.3
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• pp.373-379
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• 2015

In this paper, we propose an online VQ Codebook generation method for updating an existing VQ Codebook in real-time and adding to an existing cluster with newly created text data which are news paper, web pages, blogs, tweets and IoT data like sensor, machine. Without degrading the performance of the batch VQ Codebook to the existing data, it was able to take advantage of the newly added data by using a triangle inequality which modifying the VQ Codebook progressively show a high degree of accuracy and speed. The result of applying to test data showed that the performance is similar to the batch method.

• Journal of the HCI Society of Korea
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• v.10 no.1
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• pp.5-17
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• 2015

Nowadays various public data have been serviced to the public. Through the opening of public data, the transparency and effectiveness of public policy developed by governments are increased and users can lead to the growth of industry related to public data. Since end-users of using public data are citizens, it is very important for everyone to figure out the meaning of public data using proper visualization techniques. In this work, to indicate the significance of widespread public data, we consider UN voting record as public data in which many people may be interested. In general, it has high utilization value by diplomatic and educational purposes, and is available in public. If we use proper data mining and visualization algorithms, we can get an insight regarding the voting patterns of UN members. To visualize, it is necessary to measure the voting similarity values among UN members and then a social graph is created by the similarity values. Next, using a graph layout algorithm, the social graph is rendered on the screen. If we use the existing method for visualizing the social graph, it is hard to understand the meaning of the social graph because the graph is usually dense. To improve the weak point of the existing social graph visualization, we propose Friend-Matching, Friend-Rival Matching, and Bubble Heap algorithms in this paper. We also validate that our proposed algorithms can improve the quality of visualizing social graphs displayed by the existing method. Finally, our prototype system has been released in http://datalab.kunsan.ac.kr/politiz/un/. Please, see if it is useful in the aspect of public data utilization.

• The Journal of Society for e-Business Studies
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• v.23 no.2
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• pp.83-96
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• 2018

Extracting keywords representing documents is very important because it can be used for automated services such as document search, classification, recommendation system as well as quickly transmitting document information. However, when extracting keywords based on the frequency of words appearing in a web site documents and graph algorithms based on the co-occurrence of words, the problem of containing various words that are not related to the topic potentially in the web page structure, There is a difficulty in extracting the semantic keyword due to the limit of the performance of the Korean tokenizer. In this paper, we propose a method to select candidate keywords based on semantic similarity, and solve the problem that semantic keyword can not be extracted and the accuracy of Korean tokenizer analysis is poor. Finally, we use the technique of extracting final semantic keywords through filtering process to remove inconsistent keywords. Experimental results through real web pages of small business show that the performance of the proposed method is improved by 34.52% over the statistical similarity based keyword selection technique. Therefore, it is confirmed that the performance of extracting keywords from documents is improved by considering semantic similarity between words and removing inconsistent keywords.

• Spatial Information Research
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• v.18 no.4
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• pp.129-140
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• 2010

Large portal sites such as Google, NAVER provide Various services based on the map. Thus, interest and demand of users who want to obtain the region-related information has been increased. And services that combine the regional information with the map are provided currently at the large portal sites. However, the existing services of large portal sites do not provide enough detailed information and are inconvenient because acquisition process of related information is repeated. Therefore, the system that enables users to obtain detailed information related on the specific region synthetically and easily is needed. In this paper, we propose a system model using map interface and knowledge-processing in order to build the system that is useful for acquiring regional information. The model consists of 3-Layers: 'Regional Information Web-Documents Layer', 'Unique Regional Information Layer', and "Map-Interface Layer'. The Integrated Region~Related Information Searching System based on the model is implemented through the following 4-steps: (1) extracting the keywords that represent specific region (2) collecting the related web pages (3) extracting a set of related keywords and computing an association between the keywords (4) implementing a user interface. We verified validity on the model we proposed. knowledge-processing algorithm using affinity matrix, and UI that help users conveniently search by applying the system to region of the Goyang City. This system integrates regional information existing merely individual 'information' and provides users the 'knowledge' that is newly produced and organized. Users can obtain various detailed regional information and easily get related information through this system.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.11a
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• pp.23-26
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• 2023

In the past, in observing the sea fog on the major sea route and providing real-time information for the safe operation of ships, a visibility sensor or a fog detector with similar operating principles was installed to observe local fog near the place where it was installed. However, it was somewhat unreasonable to immediately provide sea fog observation information to ships and users because the reliability of real-time observation information was somewhat low due to pollution caused by dust, salt, and pollen, or malfunctions of detection sensors by organisms such as spider webs. From 2019 to 2022, the Korea Meteorological Administration and the Ministry of Oceans and Fisheries collaborated to build a more reliable real-time image-based sea fog observation system in 100 regions of the Lighthouse on major sea routes across the country to collect reliable sea fog observation information every 10 minutes and perform real-time public service(webpage).

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.1162-1165
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• 2011

본 연구는 그린하우스 내의 환경 정보를 원격 감시 및 제어함으로써, 재배의 편리성을 확보하는 한편, 수집된 정보에 대하여 데이터베이스를 구축하여 작물 재배의 최적 환경을 도출하는 데 그 목적이 있다. 이를 위해서, 2연동 그린하우스 제작하여, 그린하우스를 내에 여러 종류의 센서와 카메라를 장착하였으며, 이를 통해서 감지되는 정보를 원격에서 수집, 자료화 하였다. 사용자 편의를 위하여 웹페이지를 개설, 실시간으로 정보의 검색과 제어가 가능하게 하였으며, 모바일에서도 일부 기능 구사가 가능하도록 하였다. 정보의 수집과 전달, 사용자에 의한 그린하우스 환경제어와 관련한 모든 기능에 대한 안정성을 장시간 현장시험을 통해서 실험적으로 확인하였다. 이 시스템은 그린하우스를 설치하여 작물을 재배하는 농가에 편리를 제공하여 시간적, 공간적 제약에서 많은 융통을 부여할 것이다. 또한 공장, 사무실, 가정 등 유사한 환경 시설에 대해서 확대 적용하는 것이 가능할 것이다.