• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.602-605
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• 2003

최근, 컴포넌트 기술의 발전에 따라 웹 기반 교육 시스템에서도 이를 응용하여 다양한 교육 컨텐츠의 제공 및 활용하려는 연구가 진행되고 있다. 또한, EJB는 웹 기반 컴포넌트 모델로서 웹 기반응용 시스템부분에서 많은 관심을 받고 있다 그러나, 컴포넌트 기반 웹-코스웨어는 이용 가능한 상용 컴포넌트와 인식부족으로 아직까지 실용화되지 못하고 있는 실정이며 분석에 관한 정형화도 이루어지지 않고 있다. 따라서, 본 연구에서는 EJB 컴포넌트를 이용한 웹 코스웨어를 분석 및 구현을 하였다. 컴포넌트들 사이의 메시지 흐름에 대한 정형적인 명세 분석을 위하여 페트리 넷을 이용하였으며, 각 기능에 따라 무상태 세션 빈의 형식으로 EJB 시스템을 구현하였다.

• Information and Communications Magazine
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• v.29 no.11
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• pp.36-42
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• 2012

대부분의 빅 데이터 분석 결과는 문장으로 다듬어진 보고서로 결과를 제시하기보다는 비주얼라이제이션으로 결과를 보이고 보는 사람이 갖고 있는 배경지식과 통찰력에 따라 의미 있는 내용을 도출할 수 있도록 한다. 본 고에서는 공공 데이터와 비주얼라이제이션의 중요성을 알리기 위한 국회의원 투표 성향 분석 프로젝트를 소개한다. 우리나라 국민이라면 누구나 관심을 가질만한 국회의원의 성향을 파악하는 것을 세부 목표로 하고 18대 국회의원의 본 회의 회의록으로부터 투표 데이터를 수집하여 유사한 투표성향을 가진 국회의원을 가깝게 배치하여 누구나 쉽게 의원간의 유사성을 알 수 있도록 하였다. 데이터 수집부터 분석모델 개발과 웹 페이지를 만들기까지의 프로젝트 진행과정에서 모델의 수정이 필요했으며 왜 그러한 선택을 했는지를 설명한다.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10a
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• pp.427-429
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• 2001

웹의 발전에 따라 거대해진 웹사이트들은 서로 복잡하게 얽혀진 링크들로 인해 웹 개발과 유지보수에 큰 어려움이 따른다. 효율적인 웹 개발과 유지보수를 위해서는 웹에서 가장 중요한 정보의 단위인 링크정보들을 추출할 수 있는 방법이 요구된다. 본 논문에서는 웹 브라우저 요청에 의해 반환된 HTTP 헤더분석과 HTML 문서의 태그분석을 통해 링크들을 추출하여 “끊어진 링크”를 찾고, 추출된 “링크요소”들과 서버에 저장된 파일들을 비교하여 “사용되지 않는 파일”들을 찾아주는 “링크 분석기”시스템을 개발함으로 써 웹 개발과 유지보수에 있어서 가장 기본적이면서도 중요한 링크관리에 대한 방법을 제시한다

• Journal of the Korean Society for information Management
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• v.20 no.3
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• pp.177-197
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• 2003

The purpose of this study is to suggest the subject and standards of evaluation on integrated IR interface. For this study, we studied the preceding research about major IR interface models. We took the survey for interface elements which were verified by experts. These interface elements are divided twe viewpoints. One is the cognitive viewpoints which are the page design, content design, site design, output form, usability and aesthelic facet. The other is the objective viewpoints which are page design, dontent design, site design, output for and usability. We found that these evaluation elements have a crediblilty.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.11
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• pp.6856-6862
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• 2014

Web usage mining is a method to extract meaningful patterns based on the web users' log data. Most existing patterns of web usage mining, however, do not consider the users' diverse inclination but create general models. Web users' keywords can have a variety of meanings regarding their tendency and background knowledge. This study evaluated the extraction web-user's pattern after collecting and analyzing the web usage information on the users' keywords of interest. Web-user's pattern can supply a web page network with various inclination information based on the users' keywords of interest. In addition, the Web-user's pattern can be used to recommend the most appropriate web pages and the suggested method of this experiment was confirmed to be useful.

• The Journal of the Korea Contents Association
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• v.13 no.8
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• pp.60-71
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• 2013

The current study examines the major variables -Facebook social connectedness and brand self-disclosure- that affect the relationship between users and brands. In this study, we assume that users communicate and build relationships with brands via Facebook brand fan pages, like they do with other users. Additionally, we test the effect of attitude toward Facebook fan page on intention to be a fan of the fan page. The results show that the brand's self-disclosure positively affects on attitude toward the fan page, but Facebook social connectedness has negative effects. Also, attitude toward the fan page has positive effects on the intention to be a fan. This study helps understand how brand messages are spreading across diverse Facebook users.

• The KIPS Transactions:PartB
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• v.18B no.4
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• pp.231-240
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• 2011

Many search algorithms have been implemented by many researchers on the world wide web. One of the best algorithms is Google using PageRank technology. PageRank approach computes the number of inlink of each documents then ranks documents in the order of inlink members. But it is difficult to find the results that user needs, because this method find documents not valueable for a person but valueable for the public. To solve this problem, We use the WordNet for analysis of the user's query history. This paper proposes a personalized search engine using the user's query history and PageRank Check. We compared the performance of the proposed approaches with google search results in the top 30. As a result, the average of the r-precision for the proposed approaches is about 60% and it is better as about 14%.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.9
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• pp.617-625
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• 2009

NAND flash memory is widely used in embedded systems because of many attractive features, such as small size, light weight, low power consumption and fast access speed. However, it requires garbage collection, which includes erase operations. Erase operation is very slow. Besides, the number of the erase operations allowed to be carried out for each block is limited. The proposed garbage collection method focuses on minimizing the total number of erase operations, the deviation value of each block and the garbage collection time. NAND flash memory consists of pages of three types, such as valid pages, invalid pages and free pages. In order to achieve above goals, we use a page rate to decide when to do garbage collection and to select the target victim block. Additionally, We implement allocating method and group management method. Simulation results show that the proposed policy performs better than Greedy or CAT with the maximum rate at 82% of reduction in the deviation value of erase operation and 75% reduction in garbage collection time.

• Journal of Internet Computing and Services
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• v.20 no.3
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• pp.43-59
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• 2019

Today, with the spread of smartphones and the development of social networking services, structured and unstructured big data have stored exponentially. If we analyze them well, we will get useful information to be able to predict data for the future. Large amounts of data need to be collected first in order to analyze big data. The web is repository where these data are most stored. However, because the data size is large, there are also many data that have information that is not needed as much as there are data that have useful information. This has made it important to collect data efficiently, where data with unnecessary information is filtered and only collected data with useful information. Web crawlers cannot download all pages due to some constraints such as network bandwidth, operational time, and data storage. This is why we should avoid visiting many pages that are not relevant to what we want and download only important pages as soon as possible. This paper seeks to help resolve the above issues. First, We introduce basic web-crawling algorithms. For each algorithm, the time-complexity and pros and cons are described, and compared and analyzed. Next, we introduce the state-of-the-art web crawling algorithms that have improved the shortcomings of the basic web crawling algorithms. In addition, recent research trends show that the web crawling algorithms with special purposes such as collecting sentiment words are actively studied. We will one of the introduce Sentiment-aware web crawling techniques that is a proactive web crawling technique as a study of web crawling algorithms with special purpose. The result showed that the larger the data are, the higher the performance is and the more space is saved.

• ETRI Journal
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• v.9 no.1
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• pp.165-172
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• 1987

본고에서는 컴퓨터의 출력장치로서 최근 가장 인기를 얻고 있는 논-임팩트 레이저 페이지 프린터(non-mpact laser page printer), 즉 레이저 빔 프린터(LBP : Laser Beam Printer)의 성능 및 특성에 관한 고찰과 현재 시판중인 desktop 레이저 빔 프린터를 비교 분석하고 그 응용사례에 대해서 간단히 소개하고자 한다.