• Proceedings of the Korea Database Society Conference
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• 1998.09a
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• pp.421-430
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• 1998

지식경영을 위한 다양한 대상 업무중에서 텍스트 데이터의 마이닝은 특히 중요하다. 그 이유는 텍스트 데이터가 양적인 면에서 가장 풍부하고, 또 발견할 수 있는 지식을 가장 많이 포함하고 있기 때문이다. 본 논문에서는 텍스트 데이터베이스에서 지식발견을 위한 한 과정으로 텍스트 데이터베이스 내의 텍스트들을 분류하는 기법을 기술한다. 특히 문서 분류 방법은 데이터베이스의 일부 데이터를 훈련, 예제로 간주하여 교사 학습 알고리즘을 통해 학습한 후 나머지 데이터를 이용해 분류 정확성을 검증 및 향상시킨다. 시험 데이터로는 인터넷의 뉴스그룹의 기사를 이용하였고, 시험 결과 분류의 정확성은 한글 및 영문 모두 최소 70% 이상으로 나타났다.

• Proceedings of the Korea Database Society Conference
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• 1998.09a
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• pp.83-98
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• 1998

Who needs Media Asset Management？ ◆ Publishers ◆ Any company publishing newspapers, magazines, catalogs or web sites. ◆ Content Creators ◆ Companies who create content for use in their business ◆ Broadcasters, Advertising Agencies, Studios, Sports Houses (NBA, NFL), Corporate Training Depts, Retailers ◆ Content Distributors ◆ Cable Operators, Telecoms, Internet Service Providers, Online Service Providers Who needs Media Asset Management？ ◆ There's a LOT of money being spent on this kind of technology, and not just by 'media' companies ◆ Retailers, for catalogs, web sites, call centers ◆ Chems/Pharms, for drug. discovery, knowledge management ◆ Legal, for document and knowledge management ◆ Federal, for video surveillance and knowledge management ◆ Manufacturing, for integration of CAD, text and business-to-business applications ◆ Anyone with a Web/Content Management challenge(omitted)

• Bulletin of the Korean Space Science Society
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• 1999.04a
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• pp.40-40
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• 1999

No Abstract, See Full Text

• Communications for Statistical Applications and Methods
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• v.11 no.3
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• pp.513-518
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• 2004

The well-known mode-mean-median inequality for the unimodal population distribution does not always hold for the frequency distribution. But many elementary statistics text books just mention that the relative location of the mean and median can be used to determine whether a distribution is positively or negatively skewed. In this paper we introduce the method generating data that is positively skewed but mean

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.08a
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• pp.349-352
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• 2000

본 논문은 소프트웨어-인간공학적 원칙(Soft-ware-Ergonomic principles)이 어떻게 사용자 우호적 HCI 디자인에 있어서 효율적으로 기여할 수 있는가를 보여준다. 다양한 실증적 연구를 통하여 우리는 하나의 이론적 모델(WOB-Model)을 만들었으며, 이 모델은 다수의 시스템 개발에 적용되어 그 가치가 인정되었다. 본 모델에 기초하여 디자인 된 시스템을 가지고 행한 사용자테스트(User tests)는 소프트웨어시스템에서 일반적으로 자주 나타나는(Usability pro-blems)가 없어 질 수 있음을 보여 주었다.

• Proceedings of the Zoological Society Korea Conference
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• 1999.10b
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• pp.82.1-82
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• 1999

No Abstract, See Full Text

• Proceedings of the Korea Contents Association Conference
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• 2019.05a
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• pp.227-228
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• 2019

This study examines the features of Korean EFL students' letter writing at a university in Korea. The data comprised interviews and examples of letter writing. The findings revealed that students engaged in unique ways in which they oriented their meaning-making to broad views concerning rhetorics and components. Students' approaches involved a particular context and the recontextualized English formal letter, which reflects their textual interactions in writing. This paper concludes that specific discourse communities, life-world, and learning purposes impact on students' English writing.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.04a
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• pp.214-215
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• 2022

This study analyzed the development stage and change management necessity of the construction IT system through existing research and literature review, and used WordCloud, one of the text mining techniques, to analyze current construction trends and major issues. The necessity of change management is derived by using existing research literature and construction-related social issues as analysis data.

• Bulletin of the Korean Space Science Society
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• 2000.04a
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• pp.42-42
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• 2000

No Abstract, See Full Text

• Annual Conference of KIPS
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• 2023.11a
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• pp.526-527
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• 2023

Speech emotion recognition(SER) is one of the interesting topics in the machine learning field. By developing multi-modal speech emotion recognition system, we can get numerous benefits. This paper explain about fusing BERT as the text recognizer and CNN as the speech recognizer to built a multi-modal SER system.