• Journal of Korean Library and Information Science Society
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• v.39 no.4
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• pp.283-304
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• 2008

This is to develop Intelligent Retrieval System which can automatically present early query's category terms(association terms connected with knowledge structure of relevant terminology) through learning function and it changes searching form automatically and runs it with association terms. For the reason, this theoretical study of Intelligent Automatic Indexing System abstracts expert's index term through learning and clustering algorism about automatic classification, text mining(categorization), and document category representation. It also demonstrates a good capacity in the aspects of expense, time, recall ratio, and precision ratio.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.343-344
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• 2023

과학기술 문헌을 활용한 계량정보분석에서 학과정보의 활용은 매유 유용하다. 본 논문에서는 한국과학기술인용색인데이터베이스에 등재된 국내 학술지 논문에 출현하는 대학기관 소속 저자의 학과정보를 추출하고 데이터 정제 및 학과유형 분류 처리를 통해 학과정보 데이터셋을 구축하였다. 학과정보 데이터셋을 학습데이터와 검증데이터로 이용하여 딥러닝 기반의 자동분류 모델을 구현하였으며, 모델 성능 평가 결과는 한글 학과정보 기준 98.6%와 영문 학과정보 기준 97.6%의 정확률로 측정되었다. 향후 과학기술 분야별 지적관계 분석 및 논문 주제분류 등에 학과정보 자동분류 처리기의 활용이 기대된다.

• Journal of the Korean Society for information Management
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• v.28 no.1
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• pp.89-104
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• 2011

Large-scaled information extraction plays an important role in advanced information retrieval as well as question answering and summarization. Information extraction can be defined as a process of converting unstructured documents into formalized, tabular information, which consists of named-entity recognition, terminology extraction, coreference resolution and relation extraction. Since all the elementary technologies have been studied independently so far, it is not trivial to integrate all the necessary processes of information extraction due to the diversity of their input/output formation approaches and operating environments. As a result, it is difficult to handle scientific documents to extract both named-entities and technical terms at once. In order to extract these entities automatically from scientific documents at once, we developed a framework for scientific core entity extraction which embraces all the pivotal language processors, named-entity recognizer and terminology extractor.

• Journal of the Korea Society of Computer and Information
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• v.11 no.5 s.43
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• pp.53-58
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• 2006

In this paper, I propose an image based feature extraction method for an automatic golf swing analysis. While most swing analysis systems require an expert like teaching professional, the proposed method enables an automatic swing analysis without a professional. The extracted features for swing analysis include not only key frames such as addressing, backward swing, top, forward swing, impact, and follow-through swing but also important positions of golfer's body parts such as hands, shoulders, club head, feet, knee. To see the effectiveness of the proposed method. I tested it for several swing pictures. Experimental results show that the proposed method is effective for extracting important swing features. Further research is under going to develop an automatic swing analysis system using the proposed features.

• Journal of the Korean Society for information Management
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• v.8 no.1
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• pp.78-99
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• 1991

So far, most of Korea's newspapers indexing have been done manually using tesaurus. In recent years, however, the need for automatic indexing system has grown stronger so as for indexers to save time, efforts and money. And some newspapers have started establishing their databases along with introducing electronic newspapers and CTS. This thesis is on establishing and automatic indexing system for the full-text of the Korea Economic Daily's articles, which have been accumulated in its database, KETEL. In my thesis, I suggest methods to create a keyword file, a stopword list, an auxiliary word list and an infected word list by applying linguistic analysis methods to Hangul, taking advantage of the language's morphological peculiarity. Through these studies, I was able to reach four conclusions as follows. First, we can obtain satisfactory keywords by automatic indexing methods that were made through morphological analysis. Second, an indexer can improve the efficiency of indexing work by controlling extracted vocabulary, as syntax analysis and semantic analysis is not complete in Hangul. Third, The keyword file in this system which is made of about 20,000 most-frequently-used newspaper terms can be used in the future in compiling a thesaurus. Finally, the suggested methods to prepare an auxiliary word list and an infected word list can be applicable to designing other automatic systems.

• The KIPS Transactions:PartB
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• v.13B no.2 s.105
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• pp.155-162
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• 2006

The medical thesaurus, MeSH (Medical Subject Heading), has been used as a controlled vocabulary thesaurus for English medical paper indexing for a long time. In this paper, we propose an automatic cross language keyword assignment method, which assigns English MeSH index terms to the abstract of a Korean medical paper. We compare the performance with the indexing performance of human indexers and the authors. The procedure of index term assignment is that first extracting Korean MeSH terms from text, changing these terms into the corresponding English MeSH terms, and calculating the importance of the terms to find the highest rank terms as the keywords. For the process, an effective method to solve spacing variants problem is proposed. Experiment showed that the method solved the spacing variant problem and reduced the thesaurus space by about 42%. And the experiment also showed that the performance of automatic keyword assignment is much less than that of human indexers but is as good as that of authors.

• Journal of Digital Contents Society
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• v.16 no.4
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• pp.583-593
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• 2015

Today, caused by the growth of computer and communication technology, multimedia, especially image data are being used in different application divisions. JPEG2000 that is widely used these days provides a Region-of-Interest(ROI) technique. The extraction of ROI has to be rapidly executed and automatically extracted in a huge amount of image because of being seen preferentially to the users. For this purpose, this paper proposes a method about preferential processing and automatic extraction of ROI using the distribution of edge in the code block of JPEG2000. The steps are the extracting edges, automatical extracting of a practical ROI, grouping the ROI using the ROI blocks, generating the mask blocks and then quantization, ROI coding which is the preferential processing, and EBCOT. In this paper, to show usefulness of the method, we experiment its performance using other methods, and executes the quality evaluation with PSNR between the images not coding an ROI and coding it.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.101-104
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• 2003

본 논문은 개인용 휴대장비인 디지털카메라등을 통하여 차량의 앞/뒤 번호판을 자동인식하며 인식된 결과를 텍스트 형식으로 결과를 사용자에게 통보함은 물론, 입력된 차량의 정보를 부호화하고 통신망을 통하여 원격지 서버로 전달하고 원격지 서버는 복호화과정을 거쳐 전송된 텍스트 형태의 차량번호를 확인하여 차량에 대한 정보를 제공하는 시스템이다. 이는 급증하는 차량범죄 및 차량통제, 도난차량검거, 수배차량추적등 많은 분야에 효과적으로 사용이 가능하며 무선 및 도로교통에 많은 편의성과 효율성을 제고할 수 있다고 사료된다.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.475-477
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• 2002

자동 문서 분류는 범주 특성 벡터와 입력 문서 벡터의 유사도 비교에 의해 가장 유사한 범주를 선택하는 방법이다. 문서 분류 시스템을 구현하기 위하여 각 범주의 특성 벡터를 정보 검색 시스템의 역파일 형태로 구축하였으며, 용어 가중치를 계산하는 방법을 달리하여 문서 분류 시스템의 정확도를 실험하였다. 실험 문서는 일간지의 신문기사들을 무작위로 추출한 문서 집합을 대상으로 하였으며, 정보 검색 모델에서 보편적으로 사용되는 TF-lDF 방식이 변형된 방식에 비해 더 나은 성능을 보였다.

• Annual Conference on Human and Language Technology
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• 2000.10d
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• pp.85-88
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• 2000

대용량 말뭉치에서 이웃 음절간 공기빈도 정보를 추출하여 한글의 bigram 음절 특성을 조사하였다. Bigram 음절 특성은 띄어쓰기가 무시된 문서에 대한 자동 띄어쓰기, 어떤 어절이 띄어쓰기 오류어인지 판단, 맞춤법 검사기에서 철자 오류어의 교정 등 다양한 응용분야에서 유용하게 사용될 것으로 예상되고 있다. 본 논문에서는 한글의 bigram 음절 특성을 자동 띄어쓰기 및 입력어절이 띄어쓰기 오류어인지를 판단하는데 적용하는 실험을 하였다. 실험 결과에 의하면 bigram 음절 특성이 매우 유용하게 사용될 수 있음을 확인하였다.