• The Journal of Asian Finance, Economics and Business
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• v.9 no.10
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• pp.215-225
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• 2022

This study investigates employees' online reviews, conducts in-depth text topic mining, effectively summarizes the dimensions of employer brand value, and seeks effective ways to build employer brands from a multi-dimensional perspective. This study employs samples of employer reviews, filter keywords according to word frequency-inverse document frequency, builds a review network containing the same keywords, explore the community and summarize the theme dimensions. Simultaneously, it makes a dynamic comparison and analysis of the employer brand value dimension of different industries and enterprises. The study shows that the community exploration theme can be summarized into 11 dimensions of employer brand value, and the dimensions of employer brand value are significantly different across industries and among different enterprises within the industry. The attention to the employer brand value dimension has a significant time change. Various industries pay increasing attention to the dimension of work intensity and career development, while employers pay steady attention to the dimension of welfare benefits. The findings of this study suggest that seeking the heterogeneity of employer brand resources from the multi-dimensional differences and changes is an effective way to improve the competitiveness of enterprises in the human capital market.

• Journal of Information Technology Services
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• v.21 no.5
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• pp.65-79
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• 2022

The smart factory has spread to small and mid-size enterprises (SMEs) under the leadership of the government. Smart factory consists of a work area, an operation management area, and an industrial control system (ICS) area. However, each site is combined with the IT system for reasons such as the convenience of work. As a result, various breaches could occur due to the weakness of the IT system. This study seeks to discover the items and vulnerabilities that SMEs who have difficulties in information security due to technology limitations, human resources, and budget should first diagnose and check. First, to compare the existing domestic and foreign smart factory vulnerability classification systems and improve the current classification system, the latest smart factory vulnerability information is collected from NVD, CISA, and OWASP. Then, significant keywords are extracted from pre-processing, co-occurrence network analysis is performed, and the relationship between each keyword and vulnerability is discovered. Finally, the improvement points of the classification system are derived by mapping it to the existing classification system. Therefore, configuration and maintenance, communication and network, and software development were the items to be diagnosed and checked first, and vulnerabilities were denial of service (DoS), lack of integrity checking for communications, inadequate authentication, privileges, and access control in software in descending order of importance.

• Journal of the Korean Society for information Management
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• v.40 no.4
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• pp.279-306
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• 2023

This study analyzed bibliographic attributes related to the selection and use of reading materials based on data on books borrowed or purchased together in order to understand the properties of reading materials that have complex user needs from various perspectives. As a result of creating co-occurrence matrices of bibliographic attribute terms by dividing them into 26 sub-attribute units related to KDC main class, target reader, and user age, and performing network analyses, the details and prominent mediating role of bibliographic attributes of reading materials were identified. The results of this study will be helpful in designing facets of reading information systems, including library OPAC, in the future.

• Journal of the Korean housing association
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• v.17 no.4
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• pp.131-143
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• 2006

Nowadays, diverse mass media discovers and introduces outstanding management cases of apartment complexes to induce vital competitions of constructors and active participation of residents to apartment management. This study statistically analyzed the management issues of outstanding apartment complexes that have been introduced by mass media with lexical criteria to examine the characteristics of their exemplary management. The key issues of outstanding apartment management are summarized as: efficient management of convenient facilities for residents, community activities based on residents' participation, and maintenance of pleasant living environments through transparent management. Also, the result of the relation arrangement of co-occurrence word from a Social Network Analysis included three key concepts of multi-family housing management - Maintenance Management, Operating Management, and Community Life Management - with emphasis on 'residents' and 'apartment complexes.' However, Operating Management was relatively deemphasized.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.365-370
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• 1997

In this paper we suggest a development of surface defect inspection algorithms for cold mill strip using tree structure. The defects which exist in a surface of cold mill strip have a scattering or singular distribution. This paper consists of preprocessing, feature extraction and defect classification. By preprocessing, the binarized defect image is achieved. In this procedure, Top-hit transform, adaptive thresholding, thinning and noise rejection are used. Especially, Top-hit transform using local min/max operation diminishes the effect of bad lighting. In feature extraction, geometric, moment, co-occurrence matrix, histogram-ratio features are calculated. The histogram-ratio feature is taken from the gray-level image. For the defect classification, we suggest a tree structure of which nodes are multilayer neural network clasifiers. The proposed algorithm reduced error rate comparing to one stage structure.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1311-1314
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• 2003

In this paper, we propose a method to measure document similarity. First, we have exploited single-term method that extracts nouns by using a lexical analyzer as a preprocessing step to match one index to one noun. In spite of irrelevance between documents, possibility of increasing document similarity is high with this method. For this reason, a term-phrase method has been reported. This method constructs co-occurrence between two words as an index to measure document similarity. In this paper, we tried another method that combine these two methods to compensate the problems in these two methods. Six types of features are extracted from two input documents, and they are fed into a neural network to calculate the final value of document similarity. Reliability of our method has been proved by an experiment of document retrieval.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.283-284
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• 2006

In this paper, we propose a novel segmentation and classification method using texture features for the document image. First, we extract the local entropy and then segment the document image to separate the background and the foreground using the Otsu's method. Finally, we classify the segmented regions into each component using PCA(principle component analysis) algorithm based on the texture features that are extracted from the co-occurrence matrix for the entropy image. The entropy-based segmentation is robust to not only noise and the change of light, but also skew and rotation. Texture features are not restricted from any form of the document image and have a superior discrimination for each component. In addition, PCA algorithm used for the classifier can classify the components more robustly than neural network.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2815-2817
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• 1999

본 연구에서는 영상처리 기법을 이용하여 조각으로 나누어진 강판의 표면정보를 계산하여 표면정보를 검사하는 새로운 검사 기법을 제안한다. 이는 냉연 표면의 입력영상으로부터 wavelets 변환기법을 이유하여 영상을 정량화하고, 이 영상으로 co-occurrence 행렬을 이용하여 데이터들 간의 주된 특징들을 추출하여, 표면 정보를 인식 후 흠을 분류하기 위한 분류기로서 신경망을 이용하여분류하는 과정을 거치게 된다. 제시하는 알고리즘은 기존의 벡터양자화 기법과 비교하여 우수한 성능을 보임을 실험을 통해 입증하였으며, 실시간 구현에 효과적으로 적용될 수 있음을 보였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.459-461
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• 2024

본 논문은 국내 정보보안 분야 학술 연구에서 참고문헌 인용행태를 파악하고자 해당 분야 대표 학술지의 인용문헌 현황 및 패턴을 분석하였다. 실험데이터는 "정보보호학회논문지"를 대상으로 수록된 모든 논문과 참고문헌 정보를 수집하고 개별 학술지 및 학술대회의 식별 과정을 통해 구축하였다. 이를 기반으로 참고문헌 현황, 인용나이 통계 분석 결과와 동시출현네트워크 (학술지 및 학술대회)의 생성을 통한 네트워크 중심성 및 시각화 지도를 제시하였다.

• Journal of the Korean Society for information Management
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• v.38 no.1
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• pp.53-69
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• 2021

This study aims to understand the research landscape of South Korea using the data of 2020 Google Scholar Metrics. To achieve the goal, we constructed and analyzed four types of networks including the university collaboration network, the keyword co-occurrence network, the journal citation network, and the discipline citation network. Through the analysis of the university collaboration network, we found major universities such as Seoul National University, Keimyung University, and Sungkyunkwan University that have led collaborative research. Job related keywords such as job change intention and job satisfaction have been frequently studied with other keywords. Through the analysis of the journal citation network, we found multiple journals such as The Journal of the Korea Contents Association, Korean Journal of Sociology, and Korean Journal of Culture and Social Issues that have been widely cited by the other journals and influenced them. Finally, Education, Business administration, and Social welfare were identified as the top influential disciplines that have influenced other disciplines through the knowledge diffusion. The study is the first of its kind to use the data of Google Scholar Metrics and conduct a stepwise network analysis (e.g., keyword, journal, and discipline) to broadly understand the research landscape of South Korea. Our results can be used by government agencies and universities to develop effective strategies of promoting university collaboration and interdisciplinary research.