• 한국문헌정보학회지
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• 제17권
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• pp.339-366
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• 1989

Appearance of full-text online is the most encouraging phenomenon ·during the development of databases. The full-text databases of today is derived from by-product of electronic publication of printed materials. Now, there are also some movements toward electronic production of documents in Korea although not powerful. The present study is designed to examine the characteristics and effective retrieval method of full-text databases now commercially available through various vendors. The outline of this paper IS as follows: First, background and present situation of existing full-text database services through national and worldwide are examined. Second, free-text searching system of full-text databases is compared with controlled vocabulary system. The factors influencing on free-text retrieval performance, searching thesaurus, and hybrid or compromising system, which is using limited controlled vocabulary in conjunction with natural language for the enrichment needed for practical operation of the . system, are examined. Third, user demands through the analysis of preceding studies on 'various types of full-text databases are recognised. Fouth, application of CD-ROM full-text database to the libraries and information centers is examined as prospective resources for them. Finally, some problems and prospect of full-text databases are presented.

• Journal of Computing Science and Engineering
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• 제6권2호
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• pp.168-177
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• 2012

The search for relevant and actionable information is a key to achieving clinical and research goals in biomedicine. Biomedical information exists in different forms: as text and illustrations in journal articles and other documents, in images stored in databases, and as patients' cases in electronic health records. This paper presents ways to move beyond conventional text-based searching of these resources, by combining text and visual features in search queries and document representation. A combination of techniques and tools from the fields of natural language processing, information retrieval, and content-based image retrieval allows the development of building blocks for advanced information services. Such services enable searching by textual as well as visual queries, and retrieving documents enriched by relevant images, charts, and other illustrations from the journal literature, patient records and image databases.

• 한국콘텐츠학회논문지
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• 제5권2호
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• pp.229-242
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• 2005

우리는 스캔된 한글 문서 영상에 대한 전문(full-text) 검색 시스템을 구축하였다. 이 시스템은 크게 전처리부, 인식부, 그리고 검색부로 구성되어 있다 검색 알고리즘은 k순위까지의 인식 결과를 이용한다. 이 방법은 검색 성능이 인식 오류에 둔감할 뿐만 아니라, 재현률과 정확률을 사용자가 조절할 수 있는 장점을 갖는다. 객관적인 성능 평가를 위해 KISTI가 제공하는 정보과학회 논문지 영상을 실험에 사용하였다. 인식과 검색 성능을 통하여 시스템이 실용적임을 보였다.

• 한국멀티미디어학회논문지
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• 제1권2호
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• pp.162-172
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• 1998

본 논문에서는 영문 텍스트 검색 엔진인 MG(Managing Gigabytes) 시스템과 한글 형태소 분석기 HAM (Hangul Analysis Module)을 이용하여 기가바이트 크기의 텍스트 데이타 처리가 가능한 한글 텍스트 검색 엔진 HMG(Hangul MG)를 구현하였다. 한글 처리를 위해 KSC 5601 완성형 코드를 사용하여 데이타베이스 구축 단계와 질의 처리 단계에서 사용하였다. HMG의 개발을 위해 MG 시스템의 렉시칼 분석기와 파서, 인텍스 구성 모률을 수정하였다. HMG 시스템의 유용성을 보이기 위해 웹에서 한글 소설을 검색할 수 있도록 하는 N NOD (Novel On Demand) 시스템올 구현하였다. HMG 시스템은 한글이 포함된 대규모 전문 검색 시스템의 구축에 활용될 수 있다.

• Journal of Information Processing Systems
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• 제5권3호
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• pp.159-166
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• 2009

As shown in Wikipedia, tagging or cross-linking through major keywords in a document collection improves not only the readability of documents but also responsive and adaptive navigation among related documents. In recent years, the Semantic Web has increased the importance of social tagging as a key feature of the Web 2.0 and, as its crucial phenotype, Tag Cloud has emerged to the public. In this paper we provide an efficient method of automated in-text keyword tagging based on large-scale controlled term collection or keyword dictionary, where the computational complexity of O(mN) - if a pattern matching algorithm is used - can be reduced to O(mlogN) - if an Information Retrieval technique is adopted - while m is the length of target document and N is the total number of candidate terms to be tagged. The result shows that automatic in-text tagging with keywords filtered by Information Retrieval speeds up to about 6 $\sim$ 40 times compared with the fastest pattern matching algorithm.

• International Journal of Contents
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• 제2권1호
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• pp.22-28
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• 2006

In this paper, we propose new semantic contents modeling using individual features, associative relations and visual features for efficiently supporting browsing and retrieval of video semantic contents. And we implement and design a browsing and retrieval system based on the semantic contents modeling. The browsing system supports annotation based information, keyframe based visual information, associative relations, and text based semantic information using a tree based browsing technique. The retrieval system supports text based retrieval, visual feature and associative relations according to the retrieval types of semantic contents.

• 정보관리학회지
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• 제32권3호
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• pp.277-293
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• 2015

본 논문에서는 문헌의 적합성수준을 적합성정도에 따라 4그룹(부적합한, 조금 적합한, 적합한, 매우 적합한)으로 나눈 후 서로 다른 심사자가 적합성 판정을 내린 4개의 적합성 판정세트(A, B, C, D)에서 "조금 적합한" 문헌을 부적합문헌으로 분류했을 때와 적합문헌으로 분류하였을 때에, 초록/표제 시스템과 전문검색시스템에서 적합성피드백으로 인한 검색효율성의 증진은 어느 쪽이 더 혜택을 받게 되는 지를 연구하였다. "조금 적합한" 문헌을 적합문헌으로 포함시켰을 때 초록/표제시스템이 전문검색시스템보다 모든 적합성판정세트에서 검색효율성의 증가율이 높았고, 반면에 전문검색시스템에서는 "조금 적합한" 문헌을 적합문헌그룹에서 제외시켰을 때 검색효율성의 증가율이 일관성 있게 높아지는 것을 발견하였다. 이는 전문검색시스템에서는 적합문헌으로 포함된 "조금 적합한" 문헌으로부터 얻어지는 적합성피드백 정보는 잡음의 역할을 하게 되어 검색효율성의 증진에 도움이 안 되고 있음을 암시하고 있다. 특히, 매우 동질적인 문헌을 색인 및 검색대상으로 하고 있는 전문검색시스템에서는 잡음에 의해 초래되는 낮은 정확률을 개선하는 정교한 검색기법에 대한 연구가 지속되어야만 한다.

• 대한의용생체공학회:의공학회지
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• 제36권3호
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• pp.55-60
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• 2015

An effective image retrieval system is required as the amount of medical imaging data is increasing recently. Authors reviewed the recent development of text-based medical image retrieval including the use of controlled vocabularies - RadLex (Radiology Lexicon), FMA (Foundational Model of Anatomy), etc - natural language processing, semantic ontology, and image annotation and markup.

• International Journal of Knowledge Content Development & Technology
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• 제7권1호
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• pp.101-120
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• 2017

Healthcare professionals have edited many health questions (HQs) and their answers for healthcare consumers on the Internet. The HQs provide both readable and reliable health information, and hence retrieval of those HQs that are relevant to a given question is essential for health education and promotion through the Internet. However, retrieval of relevant HQs needs to be based on the recognition of the intention of each HQ, which is difficult to be done by predefining syntactic and semantic rules. We thus model the intention recognition problem as a text classification problem, and develop two techniques to improve a learning-based text classifier for the problem. The two techniques improve the classifier by location-based and area-based feature weightings, respectively. Experimental results show that, the two techniques can work together to significantly improve a Support Vector Machine classifier in both the recognition of HQ intentions and the retrieval of relevant HQs.

• 정보관리학회지
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• 제16권3호
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• pp.49-63
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• 1999

본 연구는 질문용어의 분포가 초록/표제 및 전문으로 표현된 문헌 내에서 2-포아송 분포를 따르고 있는지를 조사하였으며 질문용어의 2-포아송 분포여부가 확률이론에 기반을 둔 이진독립모형과 2-포아송 독립모형에서 초록/표제 및 전문의 검색효율성에 미치는 영향을 비교 분석하였다.