• Annual Conference on Human and Language Technology
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• 2008.10a
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• pp.96-102
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• 2008

자연언어처리에서 어휘의 의미를 구분하는 것은 기계번역이나 정보검색과 같은 여러 응용 분야에서 매우 중요한 역할을 한다. 국내에서도 여러 어의 중의성 해소 시스템이 소개되었으나 대부분 시스템이 의미 부착 말뭉치를 이용한 감독 학습 방식을 기반으로 두고 있다. 본 논문은 한국어 어휘의미망을 이용한 비감독 어의 중의성 해소 시스템을 소개한다. 일반적으로 감독어의 중의성 해소 시스템은 비감독 어의 중의성 해소 시스템보다 성능은 좋으나 대규모의 의미 부착 말뭉치가 있어야 한다. 그러나 본 시스템은 한국어 어휘의미망과 의미 미부착 말뭉치에서 추출한 어휘 통계정보를 이용해, 의미 부착 말뭉치에서 추출한 의미별 통계 정보를 이용하는 감독 중의성 해소 방법과 같은 효과를 낸다. 본 시스템과 타 시스템의 성능 비교를 위해 'SENSEVAL-2' 평가 대회의 한국어 평가 데이터를 이용하였다. 실험 결과는 추출된 통계 정보를 바탕으로 우도비를 이용하였을 때 정확도 72.09%, 관계어 가중치를 추가로 이용하였을 때 정확도 77.02%로 감독 중의성 해소 시스템보다 높은 성능을 보였다.

• Digital Contents
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• no.5 s.96
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• pp.36-41
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• 2001

데이터웨어하우스(Dataware House)가 자료 창고라고 하면 데이터마이닝(Data mining)은 그 창고에 있는 데이터를 가지고 실제 분석을 하는 것이다. 창고에 있는 데이터 자체는 기업에 부가가치를 줄 수는 없다. 이것을 분석하여 유용한 자료가 나와야지 그것을 가지고 행동에 옮겨 기업은 이익을 얻기 때문이다. 예를 들면 아무리 야구에 대한 지식이 머리 속에 많은 감독이라도 고민을 하여 실제 경기에서 응용할 수 있는 작전이 없다면 그 지식은 의미가 없듯이 데이터가 아무리 훌륭하고 많아도 그것을 분석하는 단계에서 문제가 있다면 아무 소용이 없다는 것이다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.24 no.6
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• pp.1293-1308
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• 2014

The cause of privacy extrusion in credit card company at 2014 is usage of the original data in test system. By Electronic banking supervision regulations of the Financial Supervisory Service and Information Security business best practices of Finance information technology (IT) sector, the data to identify the customer in the test system should be used to convert. Following this guidelines, Financial firms use converted customer identificaion data by loading in test system. However, there is some risks that may be introduced unintentionally by user mistake or lack of administrative or technical security in the process of testing. also control and risk management processes for those risks did not studied. These situations are conducive to increasing the compliance violation possibility of supervisory institution. So in this paper, we present and prove the process to eliminate the compliance violation possibility of supervisory institution by controlling and managing the unidentified conversion customer identification data and check the effectiveness of the process.

• Korean Journal of Remote Sensing
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• v.15 no.1
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• pp.39-50
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• 1999

It is complicate and time-consuming process to classify a multi-band satellite imagery according to the application. In addition, classification rate sensitively depends on the selection of training data set and features in a supervised classification process. This paper introduced a classification network adopting a fuzzy-based $\gamma$-model in order to select a training data set and to extract feature which highly contribute to an actual classification. The features used in the classification were gray-level histogram, textures, and NDVI(Normalized Difference Vegetation Index) of target imagery. Moreover, in order to minimize the errors in the classification network, the Gradient Descent method was used in the training process for the $\gamma$-parameters at each code used. The trained parameters made it possible to know the connectivity of each node and to delete the void features from all the possible input features.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.6
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• pp.195-208
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• 2022

The role of venture CEO and their intrinsic capabilities on organizational performance can be determined by the level of resource synchronization initiated by the focal managers. Despite the important role of venture CEOs, a systematic lack of in-depth theoretical and empirical studies on ruminating the relationship between the effects of a CEO's capabilities and organizational performance depending on the level of resource synchronization exist for the rationale of investigation. To supplement the limitations of previous studies, this research empirically analyzes the role of managers specifically synchronizing organizational resources that affect organizational performance in the professional sports industry. Based on the entrepreneurship theory and resource-based view (RBV), this research conceptualizes the roles of venture CEO and basketball head coach in the professional sports industry as very similar in terms of organizational structure and performance mechanism embedding entrepreneurial characteristics necessary for managing organizational resources. In this research, we hypothesized (1) organizational resource synchronization will mediate the positive relationship between the ability of professional basketball head coach and organizational performance and (2) the indirect effect of the professional basketball head coach's capabilities on organizational performance mediated by resource synchronization will be moderated by the capabilities of players. To test these hypotheses, we utilized the PROCESS macro model 58 with the empirical data of 9 seasons (2013~2014-2021~2022) of 30 National Basketball Association (NBA) and 10 Korean Basketball League (KBL) teams. The statistical results showed that (1) resource synchronization mediates the positive relationship between professional basketball head coach capabilities and organizational performance and (2) the capabilities of players moderated the indirect effects of the abilities of head coaches on team performance via resource synchronization. This paper contributes to both academic and practical domains of entrepreneurship by empirically testing the research model through objective professional sports data.

• Journal of the Korea Convergence Society
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• v.10 no.7
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• pp.191-198
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• 2019

This paper investigates different types of leadership found in foreign coaches in charge of the Korean national soccer team. To that end, news articles published during the tenure of those coaches were crawled for analysis. The analysis highlighted the following results. First, successful sports leaders showed their own specific types of leadership. Second, failed sports leaders showed specific types of leadership. The findings have the following implications. The leadership established based on the analysis results have practical implications in that they suggest the types of effectiveness leadership that are required of sports leaders in managing and leading athletes whilst generating tangible results and performance.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.670-671
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• 2013

빅데이터 환경에서 개인정보가 포함된 데이터가 공개될 경우 많은 프라이버시 문제를 야기할 수 있다. 따라서, 본 논문에서는 데이터 공개 시에 개인정보를 보호하기 위한, 공개정보 안전성 검증 체계를 제안한다. 제안하는 검증 체계는 개인정보가 포함된 공개정보에 대하여 익명화 수행을 지원하고, 익명화된 데이터에 대하여 비익명화를 수행하는 등 공개정보에 대한 안전성을 평가하고, 이를 관리 감독하는 체계이다. 안전성 검증은 공개되는 정보에 따라서 다양하게 이루어 질 수 있으며, 검증의 강도에 따라서 안전성 인증 레벨을 차등 부여한다. 제안하는 체계는 빅데이터 환경에서 데이터 공개 시 개인정보보호를 위한 최소한의 안전성 보장체계라 할 수 있으며, 제안하는 체계를 통하여 빅데이터 환경에서 개인정보에 안전한 데이터 공개 환경이 조성될 것으로 기대한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.4
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• pp.492-497
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• 2005

Feature extraction is important to classify data with large dimension such as image data. The representative feature extraction methods lot feature extraction ate PCA, ICA, LDA and MLP, etc. These algorithms can be classified in two groups: unsupervised algorithms such as PCA, LDA, and supervised algorithms such as LDA, MLP. Among these two groups, supervised algorithms are more suitable to extract the features for classification because of the class information of input data. In this paper we suggest a new feature extraction algorithm PCA-FX which uses class information with PCA to extract ieatures for classification. We test our algorithm using Yale face database and compare the performance of proposed algorithm with those of other algorithms.

• Journal of the Korean Data and Information Science Society
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• v.21 no.5
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• pp.883-890
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• 2010

Illegal waste dumping is one of the major problems that the government agency monitoring water quality has to face. One solution to this problem is to find an efficient way of managing and supervising the water quality under various kinds of conditions. In this article we establish WQMA (water quality monitoring algorithm) based on the time series intervention model. It turns out thatWQMA is quite successful in detecting illegal waste dumping.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.10a
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• pp.153-157
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• 2004

본 논문은 패턴인식을 위해 사용할 수 있는 감독학습을 이용한 supervised IAFC neural network 1과 supervised IAFC neural network 2를 제안하였다 Supervised IAFC neural network 1과 supervised IAFC neural network 2는 LVQ(Learning Vector Quantization)를 퍼지화한 새로운 퍼지 학습법칙을 사용하고 있다. 이 새로운 퍼지 학습 법칙은 기존의 학습률 대신에 퍼지화된 학습률을 사용하고 있는데, 이 퍼지화된 학습률은 조건 확률을 퍼지화 한 것에 근간을 두고 있다. Supervised IAFC neural network 1과 supervised IAFC neural network 2의 성능과 오류역전파 신경회로망의 성능을 비교하기 위하여 iris 데이터를 사용하였는데, 실험결과 supervised IAFC neural network 2 의 성능이 오류역전파 신경회로망의 성능보다 우수함이 입증되었다.