• Journal of the military operations research society of Korea
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• v.36 no.1
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• pp.39-49
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• 2010

This paper tries to identify emerging defense technology using S&T Text Mining. As a national agenda, there has been much effort to build S&T information systems including NTIS and DTiMS that enable researchers, policy makers, or field users to analyze technological changes and promote the best policy practices for efficient workflow, knowledge sharing, strategy development, or institutional competitiveness. In this paper, the S&T Text Mining application to unmanned combat technology using INSPEC DB is empirically illustrated and shows that it is a feasible approach to identify emerging defense technology as well as the structure of knowledge network of the future technology candidates.

• Archives of design research
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• v.16 no.2
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• pp.15-22
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• 2003

This is a study on the roles in the association of sound as subtext for animation. On this study, it will be helpful to develop sound concepts and to create animations with creativity. For animation without sound can be produced as an artistic purpose, however, most animations are created with sound. It is not means that sound is less important than visual in animations. Sound is also one of significant element to create animations. Sound have many important rolls for subtext such as parts of action, leitmotif, characteristic, time, ethnic, localization in the animations. It will be analyzed two animations such as Shrek (DreamWorks Pictures production/ Director: Andrew Adams) and Monsters Inc. (Walt Disney Pictures/ Director: Peter Doctor).

• Journal of the Korean Society for information Management
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• v.26 no.3
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• pp.169-188
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• 2009

The study proposed the algorithm for automatically summarizing the audio information from a video and then conducted an experiment for the evaluation of the audio extraction that was constructed based on the proposed algorithm. The research results showed that first, the recall and precision rates of the proposed method for audio summarization were higher than those of the mechanical method by which audio extraction was constructed based on the sentence location. Second, the proposed method outperformed the mechanical method in summary making tasks, although in the gist recognition task(multiple choice), there is no statistically difference between the proposed and mechanical methods. In addition, the study conducted the participants' satisfaction survey regarding the use of audio extraction for video browsing and also discussed the practical implications of the proposed method in Internet and digital library environments.

• The Journal of the Korea Contents Association
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• v.15 no.3
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• pp.499-507
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• 2015

This study aims to understand the phenomenon related to private schools and present the implication for policy about private school, network text analysis about newspaper editorials in conservative and progressive media was conducted. The main results are as follows. First, in newspaper editorials, there were many issues about private university and there was a distinction between private elementary secondary school and private university. Second, in newspaper editorials, 'encouraging perspective' such as financial assistance and new private school like self-governing private high school and 'controlling perspective' such as withdrawal of problem private schools were both appeared. As a result, this study presents that the perspective for private schools needs to be re-established by 'accountability' as the educational institution and 'school capacity building' away from the past frame.

• The Journal of Society for e-Business Studies
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• v.19 no.2
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• pp.95-108
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• 2014

Opinion Mining is one of the application domains of text mining which extracting opinions from documents, and much researches are currently underway. Most of related researches focused on the sentiment classification which classifies the documents into positive/negative opinions. However, there is a little interest in extracting the features characterizing the individual product. In this paper, we propose the technique classifying the opinion documents according to the product features, and selecting the those features characterizing each product. In the proposed method, we utilize the document clustering technique and develope a new algorithm for evaluating the similarity between documents. In addition, through experiments, we prove the usefulness of proposed method.

• Journal of the Korea Convergence Society
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• v.11 no.1
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• pp.359-367
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• 2020

The purpose of this study is to explore text data of nursing start-up. 55 literatures were extracted from MEDLINE, Embase and Cochrane Library Data BASE. Text network analysis applied by using python network program. Key words with highest frequency and degree centrality were 'business', 'care', 'nursing', 'healthcare', 'service'. Keywords with highest degree centrality were 'mission', 'vision', 'team'. Based on the results nursing entrepreneurship support should be provided to develop competitive nursing services reflecting the specificity and science of nursing, to strengthen business competencies essential for nursing entrepreneurship, to expand nursing expertise and to present role models. The result will serve a basement to development systematic educational program and theory in nursing start-up.

• Journal of Korean Library and Information Science Society
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• v.41 no.3
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• pp.155-183
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• 2010

A book index is a locater system that ordinarily connects a set of terms from a text of a book to the page where they occur in the book's text. The DDC Relative Index differs somewhat in both of this matters. Its terms refers to classification notations and their corresponding category statements as found in the schedule text rather than to page numbers. The index is the final equipment of a classification scheme. The index is of primary importance to any classification scheme. Therefore The purpose of this study is to analysis DDC Relative Index.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.181-183
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• 2012

최근 자연어 및 정형언어 처리, 인공지능 알고리즘 등을 활용한 효율적인 의미 기반 지식모델의 생성과 분석 방법이 제시되고 있다. 이러한 의미 기반 지식모델은 효율적 의사결정트리(Decision Making Tree)와 특정 상황에 대한 체계적인 문제해결(Problem Solving) 경로 분석에 활용된다. 특히 다양한 복잡계 및 사회 연계망 분석에 있어 정적 지표 생성과 회귀 분석, 행위적 모델을 통한 추이분석, 거시예측을 지원하는 모의실험(Simulation) 모형의 기반이 된다. 본 연구에서는 이러한 의미 기반 지식모델을 통합에 있어 텍스트 마이닝을 통해 도출된 토픽(Topic) 모델 간 통합 방법과 정형적 알고리즘을 제시한다. 이를 위해 먼저, 텍스트 마이닝을 통해 도출되는 키워드 맵을 동치적 지식맵으로 변환하고 이를 의미적 지식모델로 통합하는 방법을 설명한다. 또한 키워드 맵으로부터 유의미한 토픽 맵을 투영하는 방법과 의미적 동치 모델을 유도하는 알고리즘을 제안한다. 통합된 의미 기반 지식모델은 토픽 간의 구조적 규칙과 정도 중심성, 근접 중심성, 매개 중심성 등 관계적 의미분석이 가능하며 대규모 비정형 문서의 의미 분석과 활용에 실질적인 기반 연구가 될 수 있다.

• Smart Media Journal
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• v.7 no.4
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• pp.99-105
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• 2018

It is often the case that products or services on the market are causing problems, which hurt the business and image of the company. Responding appropriately to the problem and minimizing the damage is very important to business organizations. This study collected and analyzed the news articles related to the recall of the Galaxy Note 7, which was developed and launched by Samsung Electronics, one of the smartphone market leaders. Based on the issue lifecycle, the characteristics of the news were expressed by stages and the contents of the news were analyzed and visualized using association rules. The results of this study are expected to help business organizations to understand the changes and trends of issues and search for counter measures.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.189-191
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• 2022

In modern society, messenger services are necessary to communication with others, and criminals are no exception. In representative cases of Burning Sun Gate(2018) and NthRoom(2019), messenger data analysis was used as a smoking gun to solve these criminal cases. Therefore messenger text analytics is critical for the resolution of crimes in a modern environment. also, it takes a lot of time to analyze messenger data in the digital forensic investigation process, so researchers in text mining need to be more effective to respond with the current situation In this paper, we study various natural language preprocessing(NLP) methods according to the characteristics of instant messages to effectively proceed with NLP analysis on instant messengers.