• Journal of the Korean Society for information Management
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• v.24 no.3
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• pp.321-341
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• 2007

It will be possible to prevent the infringement of the trademarks and the insueing disputes regarding the originality of the trademarks by using an efficient content-based trademark image retrieval system. In this paper, we describe a content-based image retrieval system using the Self Organizing Map(SOM) algorithm. The SOM algorithm utilizes the visual features, which were derived from the gray histogram representation of the images. In addition, we made the objective effectiveness evaluation possible by coming up with a quantitative measure to gauge the effectiveness of the content-based image retrieval system.

• Journal of Science Education
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• v.36 no.1
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• pp.49-55
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• 2012

The purpose of this study is to examine how online knowledge-based search service is being used by students in science education. Reviewing information and summarizing data are important parts in scientific inquiry. As more and more information is available online, how to review and summarize online information for scientific inquiry also becomes an issue. In this study, we examined one of the popular online knowledge-based search services to see what kinds of information in secondary school chemistry are mostly sought and how reliable those information could be. The result indicated that users mostly seek scientific explanations and problem solving but about 30% of provided information appeared to be incorrect. It implicates that it is necessary to pay attention for teaching students how to obtain, evaluate, and communicate online information in science education to enhance students' ability for scientific inquiry.

• Annual Conference on Human and Language Technology
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• 1999.10e
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• pp.20-27
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• 1999

본 논문은 정보검색 시스템 평가에 필요한 한국어 문서집합 구축과 적합 문서리스트(relevance file) 생성에 관한 기법을 문서 수집과정부터 평가작업까지 상세히 기술한다. 문서집합은 일반, 사회과학, 과학기술 분야에서 각각 4만 건으로 영역별로 균등히 구축하였으며, 질의 집합도 각 분야에 대해 10개씩 할당하여 총 30개의 질의 집합을 생성하였다. 또한 질의집합은 사용자의 수준을 고려하여 일반인, 영역 전문가, 중고등학생에 해당하는 질의를 생성함으로써 특정 영역, 특정 사용자에 독립적인 문서집합 및 질의집합을 구축하고자 하였다. 생성된 질의를 사용하여 여러 검색기에서 총 38가지의 방법으로 검색을 실시하였으며, 검색결과를 바탕으로 각 질의당 500개의 문서로 이루어진 후보 결과집합을 만든 후 이들을 대상으로 각 질의에 대한 문서의 적합성 평가를 실시하였다. 이 과정을 통해 생성된 적합문서 집합의 유효성을 보이기 위해 후보 문서 리스트 이외의 문서집합에서 적합문서가 존재할 가능성을 확인하였는데 그 방법으로 후보 리스트의 개수 증가에 따른 적합문서 개수의 변동 추세를 알아보았다. 현재 질의 개수를 50개로 확장하는 방향으로 테스트 컬렉션 구축에 대한 연구를 진행 중에 있으며, 일본 NACSIS와의 질의 교환을 통해 질의 개수를 확장할 뿐만 아니라 일본어 질의 또는 한국어 질의에 대해서 한국어 문서, 일본어 문서를 각각 검색할 수 있는 한일 교차언어 문서검색 환경을 구축하고 있다.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06a
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• pp.345-346
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• 2008

멀티미디어 데이터베이스의 효과적인 내용 기반 검색을 위한 많은 색인 방법들이 연구되어왔지만 정작 동일한 데이터 집합과 동일한 평가 기준으로 서로 다른 검색 방법들의 성능을 분석한 실험은 이뤄지지 않았다. 본 논문에서는 기존의 대표적인 색인 방법들을 구현하고 공통의 데이터 집합에 대한 색인 검색을 여러 성능 측정 기준에 따라 분석함으로써 각 색인 방법들의 특징 및 성능을 객관적으로 평가하였다. 향후 본 논문에서 실험한 결과들을 이용하면 특정 데이터 집합에 효과적인 색인 방법을 선택할 수 있을 것이다.

• Journal of Convergence for Information Technology
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• v.10 no.1
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• pp.139-148
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• 2020

As the internet and computer technology are developed, there is a need for service of traditional culture that can effectively search and create culture, history, and tradition-related materials in online contents. In this paper, we developed an RDF-based ontology retrieval service platform and verified usability and validity. This platform is divided into triple search, keyword search, network graph search, story search and management, curation management module. Based on this, the search results can be visualized based on the relationship between data, network graph search and story search can be used to easily understand the relationship between the keywords. An platform evaluation was conducted for verification, and it was evaluated that an intelligent search that can easily identify the relationship between information and shorten the analysis and search time than the existing search function.

• Journal of the Korea Computer Industry Society
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• v.7 no.5
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• pp.537-544
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• 2006

Image Search is one of the most exciting and fast growing research areas in the filed of multimedia technology. This paper conducts an empirical evaluation of color descriptor that uses the information of color distribution in color images, which is the most basic element for image search. With the experimental results, we observe that in the top 10% of precision, HSV, Daubechies 9/7 and 2 level decomposition have little better than others. Also histogram quadratic metrics outperform the Minkowski form distance metrics in similarity measurements, but spend more than 20 in computational times.

• Journal of Korean Library and Information Science Society
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• v.42 no.1
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• pp.325-338
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• 2011

This study aims to investigate characteristics of most clicked documents of Naver's universal search service. In particular, this study analyzed characteristics of most clicked documents such as click ratio, collection distribution, and yearly distribution. Also, clicked documents were evaluated in terms of relevance, credibility, and currency. In conducting this study, query logs and click logs of unified search service were analyzed. The results of this study show that most clicks occurred in blog collection and average click concentration rate reached almost 50%. Also, the relevance and currency of most clicked documents were quite high, but credibility of these documents were on average level. The results of this study can be implemented to the portal's effective development of searching algorithm and interface.

• The Journal of Society for e-Business Studies
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• v.11 no.3
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• pp.35-51
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• 2006

Information visualization plays an important role to provide a conceptual comprehension of the information and should be adjusted and featured to reflect the characteristics of the domain to which it is applied. Product searching in e-Commerce is not an exception. In this paper, we present visualization techniques that are specified for effectively browsing the results of product searching. We considered visualization techniques including MapNet and Cluster Map and modified them to reflect the characteristics of the product domain. We consider two types of search queries: category searching and product property searching, and make it possible to include more detailed product semantics in their search criteria. We also provide a query refinement mechanism so that even users with rack of understanding the products may rewrite their queries for better results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.4
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• pp.1468-1474
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• 2010

The establishment of a successful business must be preceded by comprehensive entrepreneurial preparation and research, as well as the development of a truly attractive business idea. Research to-date has tended to be based solely on factors relating to entrepreneurial activity or business performance. Research into the development and evaluation of a business idea has been insufficient. The purpose of this research is to propose a methodology for evaluating the attractiveness of a business idea objectively. This research measures the attractiveness of a business idea by the click through rate (CTR) to a website generated by specific keyword entry into internet search engines. The attractiveness of a business idea can be presented by the formula: number of relevant keyword searches x CTR on search results. As the number of searches for individual keywords is published by the search engines and it is possible to estimate CTRs for specific search results, we can objectively evaluate the attractiveness of a business idea. By analyzing keyword search data and CTRs obtained from search engines over a one month period, 1124 keywords that relate to foreign language education have been identified. A regression formula has also been derived, predicting the click through rate for search results. This research and its findings can be used to raise the success rates of new businesses; proposing objective guidelines for business idea development and evaluation. It is particularly meaningful because it introduces a new methodology to the arena.

• The Korean Journal of Applied Statistics
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• v.13 no.1
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• pp.1-10
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• 2000

정보화사회에서 효율적인 정보검색(information retrieval)은 각종 의사결정에 매우 중요하다. 주어진 정보검색 문제가 있을 때 과거에 검색되었던 자료는 그 적절성 여부에 대한 평가를 데이터베이스에 첨가하여 지식베이스(knowledge base)화 할 수 있다. 본 연구는 이 지식베이스에 대한 논리적 패턴을 분석하여 새로운 정보의 '적정성(relevance)' 여부를 판별하는 확률화 정보검색 모형을 만들고 이에 대한 실험을 하였다.