• Journal of Technology Innovation
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• v.26 no.4
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• pp.199-232
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• 2018

There are increasing needs for understanding and fathoming of business management environment through big data analysis at industrial and corporative level. The research using the company disclosure information, which is comprehensively covering the business performance and the future plan of the company, is getting attention. However, there is limited research on developing applicable analytical models leveraging such corporate disclosure data due to its unstructured nature. This study proposes a text-mining-based analytical model for industrial and firm level analyses using publicly available company disclousre data. Specifically, we apply LDA topic model and word2vec word embedding model on the U.S. SEC data from the publicly listed firms and analyze the trends of business topics at the industrial and corporate levels. Using LDA topic modeling based on SEC EDGAR 10-K document, whole industrial management topics are figured out. For comparison of different pattern of industries' topic trend, software and hardware industries are compared in recent 20 years. Also, the changes of management subject at firm level are observed with comparison of two companies in software industry. The changes of topic trends provides lens for identifying decreasing and growing management subjects at industrial and firm level. Mapping companies and products(or services) based on dimension reduction after using word2vec word embedding model and principal component analysis of 10-K document at firm level in software industry, companies and products(services) that have similar management subjects are identified and also their changes in decades. For suggesting methodology to develop analysis model based on public management data at industrial and corporate level, there may be contributions in terms of making ground of practical methodology to identifying changes of managements subjects. However, there are required further researches to provide microscopic analytical model with regard to relation of technology management strategy between management performance in case of related to various pattern of management topics as of frequent changes of management subject or their momentum. Also more studies are needed for developing competitive context analysis model with product(service)-portfolios between firms.

• Journal of Korea Multimedia Society
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• v.23 no.7
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• pp.883-890
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• 2020

In this paper, we propose a variational expectation-maximization algorithm that computes posterior probabilities from Latent Dirichlet Allocation (LDA) model. The algorithm approximates the intractable posterior distribution of a document term matrix generated from a corpus made up by 50 papers. It approximates the posterior by searching the local optima using lower bound of the true posterior distribution. Moreover, it maximizes the lower bound of the log-likelihood of the true posterior by minimizing the relative entropy of the prior and the posterior distribution known as KL-Divergence. The experimental results indicate that documents clustered to image classification and segmentation are correlated at 0.79 while those clustered to object detection and image segmentation are highly correlated at 0.96. The proposed variational inference algorithm performs efficiently and faster than Gibbs sampling at a computational time of 0.029s.

• Journal of the Korean Home Economics Association
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• v.38 no.7
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• pp.153-165
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• 2000

The purpose of this article is to document the trend in studies on the role of the father. A large number of studies on parent-child relationships have been focused on the nature of mother-child relationships. Since the 1970s, the role of the father has become an increasingly popular topic in the U.S and Japan. Why has the father's role been forgotten for such a long time\ulcorner Why is the father's role being rediscovered in recent years\ulcorner Does the father have significant impact on child's development\ulcorner This proper reviews these issues in terms of sociocultural background, trends, and future implications of the studies. A comparison and determinants analysis regarding the extent of father-child interaction, of the lather's behavior, and its effects on the child in the U.S and Japan is provided.

• Child Health Nursing Research
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• v.7 no.3
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• pp.298-307
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• 2001

This study assessed behavioral characteristics of 73 normal neonates in Daegu area using the NBAS. Being one of few studies on this topic, the study is to document and to accumulate data on the neonatal behaviors of Korean babies. Overall scores were at moderate levels in 6 behavioral clusters including Habituation, Social Interactive, Motor System, State Organization, and State Regulation. Autonomic Stability showed relative stableness. Scores of Orientation were higher in neonates of working mothers and rural mothers. Neonates of mothers with no abortion history have higher scores in Motor System and State Organization. Score of State Organization was higher in neonates of mothers with no habitual use of amenity during their pregnancy. Scores of Habituation and State Organization, as well as scores of Motor System with State Organization, State Regulation and Autonomic Stability were positively correlated. Scores of Habituation and State Organization indicate that babies are agreeable and even tameable that is advantageous for attachment to caregiver.

• Smart Media Journal
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• v.2 no.3
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• pp.17-22
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• 2013

The growth of the propagated NFC provides the various services with respect to internet applications, which it can be predicted from the simple internet services to the privated services. This paper proposes the clustering of information retrieval system model using NFC tag of access information for utilizing the similar information of the tag. The proposed model can search the similar information of the tag using the access information of NFC tag. In addition, it can cluster the similar retrieval information into topic cluster for utilizaing users.

• Korean Chemical Engineering Research
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• v.55 no.1
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• pp.135-140
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• 2017

This paper is on a study for discrimination on relative sequence as a most actively discussed topic in forensic document fields. This paper describes the application of the visual spectral comparator and infinite focus microscope as observation methods for overlapping region of printing and writing lines. As a result, we could categorize overlapping region images and identify the sequence of printing and writing lines by various inks.

• Journal of Information Technology Applications and Management
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• v.14 no.3
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• pp.1-14
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• 2007

Recently. interests in IT Service Management (ITSM) are increasing internationally as well as domestically. In order to realize the benefits from ITSM, it is necessary to institutionalize it as a culture of the organization through effective change management. One of the most promising approach of effective change management is a Six Sigma technique. In this study, we analyze a success case in which 6 Sigma was applied to Service Desk function which is one of the most important functions of ITSM. Through the analyses, this study aims to propose a feasible and specific approach to institutionalize ITSM. To accomplish the objective. the study analyzed specific methods of application of 6 Sigma to ITSM. performance of the project and future directions based on interview and project document/deliverable review. This study could not provide detailed performance measures due to lack of previous research on this topic and difficulty of obtaining quantitative data. However. this study has contributed to proposing a direction to institutionalize ITSM in organizations by analyzing a feasibility of 6 Sigma in implementing ITSM.

• Knowledge Management Research
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• v.19 no.4
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• pp.171-185
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• 2018

Studies on online review have carried out analysis of the rating and topic as a whole. However, it is necessary to analyze opinions on various dimensions of service quality. This study classifies reviews of healthcare services into service quality dimensions, and proposes a method to identify words that are mainly referred to in each dimension. Service quality was based on the dimensions provided by SERVQUAL, and patient reviews have collected from NHSChoice. The 2,000 sentences sampled were classified into service quality dimension of SERVQUAL and a method of extracting important keywords from sentences by service quality dimension was suggested. The RAKE algorithm is used to extract key words from a single document and an index is considered to consider frequently used words in various documents. Since we need to identify key words in various reviews, we have considered frequency and discrimination (IDF) at the same time, rather than identifying key words based only on the RAKE score. In SERVQUAL dimension, we identified the words that patients mentioned mainly, and also identified the words that patients mainly refer to by review rating.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.715-716
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• 2009

인터넷의 발전은 대량의 정보를 양산하였고, 이러한 대량의 정보 집합 내에서는 비슷한 정보가 재활용 되거나 반복되는 정보중복문제를 가지고 있다. 중복되는 정보들로부터 사용자에게 원하는 정보를 신속히 검색할 수 있도록 하는 정보 요약에 대한 필요성은 점차 증가하고 있다. 본 논문은 비음수 행렬 인수분해(NMF, non-negative matrix factorization)에 의한 문서의 의미특징을 이용하여 주제기반의 다중문서를 요약하는 새로운 방법을 제안한다. 본 논문에서는 다중문서가 포함하고 있는 문서들 간의 고유구조를 문서요약에 이용하여서 요약의 질을 높일 수 있고, 주제와 문장 간의 유사성과 다양성 고려하여서 쉽게 과잉정보를 제거하여 문장을 요약할 수 있는 장점을 갖는다.

• Journal of the Korean Society for information Management
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• v.34 no.4
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• pp.7-32
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• 2017

Recently, deep learning has been rapidly spreading as an innovative machine learning technique in various domains. This study explored the research trends of deep learning via modified ego centered topic citation analysis. To do that, a few seed documents were selected from among the retrieved documents with the keyword 'deep learning' from Web of Science, and the related documents were obtained through citation relations. Those papers citing seed documents were set as ego documents reflecting current research in the field of deep learning. Preliminary studies cited frequently in the ego documents were set as the citation identity documents that represents the specific themes in the field of deep learning. For ego documents which are the result of current research activities, some quantitative analysis methods including co-authorship network analysis were performed to identify major countries and research institutes. For the citation identity documents, co-citation analysis was conducted, and key literatures and key research themes were identified by investigating the citation image keywords, which are major keywords those citing the citation identity document clusters. Finally, we proposed and measured the citation growth index which reflects the growth trend of the citation influence on a specific topic, and showed the changes in the leading research themes in the field of deep learning.