• Journal of the Korean Society for information Management
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• v.33 no.3
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• pp.321-343
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• 2016

This study aimed to design a semi-automatic web-based pilot system 1) to build a Korean novel geo-name, 2) to update the database using automatic geo-name extraction for a scalable database, and 3) to retrieve/visualize the usage of an old geo-name on the map. In particular, the problem of extracting novel geo-names, which are currently obsolete, is difficult to solve because obtaining a corpus used for training dataset is burden. To build a corpus for training data, an admin tool, HTML crawler and parser in Python, crawled geo-names and usages from a vocabulary dictionary for Korean New Novel enough to train a named entity tagger for extracting even novel geo-names not shown up in a training corpus. By means of a training corpus and an automatic extraction tool, the geo-name database was made scalable. In addition, the system can visualize the geo-name on the map. The work of study also designed, implemented the prototype and empirically verified the validity of the pilot system. Lastly, items to be improved have also been addressed.

• The Journal of the Korea Contents Association
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• v.17 no.11
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• pp.331-341
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• 2017

As increasing the importance of the R&D strategy planning based on S&T evidence, the S&T DB was conducted to develop appropriate basic research support strategies by collecting 49 multiple-nations' statistics and information, extracting 6446 raw data, categorizing 877 indicators including 208 core indicators. An statistical and knowledge map analysis using the highly cited publication-related indicators was conducted to examine the expansion of DB utilization by demonstrating effectiveness of Korea's basic research. As a result, basic research investment have a strong influence on creating outstanding R&D outcomes and on producing a foundation of various S&T based-growth engines.

• 정보화사회
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• s.173
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• pp.51-54
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• 2005

경기활성화와 IT인프라 개선을 위해 마련한 '디지털 국력 강화대책'으로 추진중인 지식정보자원관리사업이 본격 착수된다. 정보통신부는 지난 2월 1일 올해 664억원을 투입, 과학기술.역사.교육학술분야 등의 자료 3천만건을 DB로 구축하고, 2600여명의 청년실업자에게 일자리를 제공하는 것 등을 내용으로 하는 '2005년도 지식정보자원관리사업 과제'를 확정.발표했다.

• Digital Contents
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• no.9 s.52
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• pp.5-17
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• 1997

데이터 마이닝에 관한 연구는 원래 인공지능의 기계 학습에서 시작되었으나 여기에서의 연구는 주로 그 대상이 실험실용 데이터 즉, 엄정하게 선정된 적은 데이터들에 대해서만 이루어져 왔다. 본 고에서는 2000년대 데이터베이스 응용기술로 발전하고 있는 데이터 마이닝에 관하여 그 개념, 지식 발견 기법 및 활용 등을 살펴보고 여러 마이닝 지식중에서 분류에 관한 기술 동향을 살펴본다.

• Journal of Scientific & Technological Knowledge Infrastructure
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• s.5
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• pp.67-71
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• 2001

최근에는 정보통신부에서 주관하는 '2000년도 지식정보연계 활용체제구축사업' 중 '과학기술종합정보시스템 구축' 사업의 일환으로 연구보고서 데이터베이스를 구축하였다. 이 사업은 연구보고서과제목록, 본문, 목차 및 참고문헌에 대한 데이터베이스 구축을 주요내용으로 하였으며 한국과학기술정보연구원의 과학기술종합정보시스템을 통하여 서비스하고 있다.

• Journal of Scientific & Technological Knowledge Infrastructure
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• s.1
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• pp.14-18
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• 2000

• Journal of Scientific & Technological Knowledge Infrastructure
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• s.1
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• pp.44-48
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• 2000

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1999.11a
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• pp.450-453
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• 1999

In this paper, the cooperative retrieval system to interface between users and DB, image data and knowledge-based database(KDB), being formed in a linguistic knowledge expression, of system is presented. Conventional database retrieval systems provide the data only in case that the data exactly corresponding with users' requirements exist in these systems, but don't in other cases. In order to resolve this problem, if the data users require are not in existence, this system shows the data and image information which are approximate with knowledge-based database materialized by fuzzy clustering and allocation of linguistic label.

• The KIPS Transactions:PartB
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• v.17B no.2
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• pp.125-138
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• 2010

The purpose of this research is to enhance document recognition system which is essential for developing full-text retrieval system of the document image data stored in the digital library of a public institution. To achieve this purpose, the main tasks of this research are: 1) analyzing the document image data and then developing its image preprocessing technology and document structure analysis one, 2) building its specialized knowledge base consisting of document layout and property, character model and word dictionary, respectively. In addition, developing the management tool of this knowledge base, the document recognition system is able to handle the various types of the document image data. Currently, we developed the prototype system of document recognition which is combined with the specialized knowledge base and the library of document structure analysis, respectively, adapted for the document image data housed in National Archives of Korea. With the results of this research, we plan to build up the test-bed and estimate the performance of document recognition system to maximize the utilization of full-text retrieval system.

• Journal of KIISE:Software and Applications
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• v.31 no.7
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• pp.911-921
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• 2004

Accurate minutiae extraction from input fingerprint images is one of the critical modules in robust automatic fingerprint identification system. However, the performance of a minutiae extraction is heavily dependent on the quality of the input fingerprint images. If the preprocessing is performed according to the fingerprint image characteristics in the image enhancement step, the system performance will be more robust. In this paper, we propose a knowledge-based preprocessing method, which extracts S features (the mean and variance of gray values, block directional difference, orientation change level, and ridge-valley thickness ratio) from the fingerprint images and analyzes image quality with Ward's clustering algorithm, and enhances the images with respect to oily/neutral/dry characteristics. Experimental results using NIST DB 4 and Inha University DB show that clustering algorithm distinguishes the image Quality characteristics well. In addition, the performance of the proposed method is assessed using quality index and block directional difference. The results indicate that the proposed method improves both the quality index and block directional difference.