• The Journal of Natural Sciences
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• v.8 no.1
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• pp.101-107
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• 1995

The purpose of this work is to develop automatic techniques for converting linear, paper-based documents to a non-linear format suitable for use in hypertext systems. The selected document was partially converted to hypertext manually, and a prototype was created using the rules derived from the manual conversion process. The full conversion was divided into three passes: correcting the electronic linear form of the document, generating a listing of the links in the document, and creating the hypertext document. Passes 2 and 3 were entirely automatic. From this study, it may be concluded that many classes of paper-based documents can be automatically converted to hypertext.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06c
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• pp.105-108
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• 2010

쌍방향으로 질문과 답변을 하는 커뮤니티 기반의 지식검색서비스에서는 질의를 통해 원하는 답변을 얻을 수 있지만, 수많은 사용자들이 참여함에 따라 방대한 문서 속에서 검증된 문서를 찾아내는 것은 점점 더 어려워지고 있다. 지식검색서비스에서 기존 연구는 사용자들이 생성한 데이터 즉 추천수, 조회수 등의 비텍스트 정보를 이용하거나 답변의 길이, 자료첨부, 연결어 등의 텍스트 정보 이용하여 전문가를 식별하거나 문서의 품질을 평가하고, 이를 검색에 반영하여 검색성능을 향상시키는 데 활용했다. 그러나 비텍스트 정보는 질의/응답의 초기에 사용자들에 의해 충분한 정보를 확보할 수 없는 단점이 제기 되며, 텍스트 정보는 전체의 문서를 답변의 길이, 자료 첨부등과 같은 일부요인으로 판단해야하기 때문에 품질평가의 한계가 있다고 볼 수 있겠다. 본 논문에서는 이러한 비텍스트 정보와 텍스트 정보의 문제점을 개선하기 위한 품질평가 알고리즘을 제안한다. 제안된 알고리즘을 통한 품질지수는 텍스트/비텍스트 정보와 소셜 네트워크 사용자 중앙성을 고려하여 질문에 적합하고 신뢰성 있는 답변을 랭킹화 함으로써 지식검색문서를 분별하는 지표가 되며, 이는 지식검색서비스의 성능향상에 기여를 할 수 있을 것으로 기대된다.

• Journal of the Korean Society for information Management
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• v.31 no.1
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• pp.231-250
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• 2014

Due to the recent development of Information and Communication Technologies (ICT), the amount of research publications has increased exponentially. In response to this rapid growth, the demand of automated text processing methods has risen to deal with massive amount of text data. Biomedical text mining discovering hidden biological meanings and treatments from biomedical literatures becomes a pivotal methodology and it helps medical disciplines reduce the time and cost. Many researchers have conducted literature-based discovery studies to generate new hypotheses. However, existing approaches either require intensive manual process of during the procedures or a semi-automatic procedure to find and select biomedical entities. In addition, they had limitations of showing one dimension that is, the cause-and-effect relationship between two concepts. Thus;this study proposed a novel approach to discover various relationships among source and target concepts and their intermediate concepts by expanding intermediate concepts to multi-levels. This study provided distinct perspectives for literature-based discovery by not only discovering the meaningful relationship among concepts in biomedical literature through graph-based path interference but also being able to generate feasible new hypotheses.

• The Journal of Society for e-Business Studies
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• v.23 no.2
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• pp.97-110
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• 2018

With the advent of the 4-th industrial revolution, manufacturing companies have increasing interests in the realization of smart manufacturing by utilizing their accumulated facilities data. However, most previous research dealt with the structured data such as sensor signals, and only a little focused on the unstructured data such as text, which actually comprises a large portion of the accumulated data. Therefore, we propose an association rule mining based facility error pattern extraction framework, where text data written by operators are analyzed. Specifically, phrases were extracted and utilized as a unit for text data analysis since a word, which normally used as a unit for text data analysis, is unable to deliver the technical meanings of facility errors. Performances of the proposed framework were evaluated by addressing a real-world case, and it is expected that the productivity of manufacturing companies will be enhanced by adopting the proposed framework.

• Journal of The Korean Association of Information Education
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• v.25 no.4
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• pp.633-640
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• 2021

Education related issues are social problems in which various groups and situations are intricately linked to each other. It is difficult to find issues by analyzing social phenomena related to education. Korean based text analysis can be analyzed in a quantitative. With the development of text analysis techniques, research results have been recently achieved, and it can be fully utilized to derive educational issues from text data in Korean. In this study, petition articles in the field of childcare/education were collected on the online-board of the Blue House National Petition website, and text analysis was used to derive issues in the education world. The analysis derived 6 topics through Latent Dirichlet Allocation(LDA) among topic modeling techniques. The association rules of major keywords were analyzed and visualized as graphs. In addition to deriving educational issues through the existing questionnaire, it can provide implications for future research directions and policies in that issues can be sufficiently discovered through text-based analysis methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.4
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• pp.357-364
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• 2019

As industrial information disclosure by insider's rate is around 80%, most of relevant researches explain briefly its causes are discontent of salary or human resources system. This paper scrapes texts on Jobplanet, an anonymous company review website and analyzes discontent keyword by 7 related area and their contexts to find out more details on brief causes referred above. After drawing LGG (Local Grammar Graph) by each areas with related dictionary list, this paper shows an example of concordance as a proof and several ways for human resources leakage prevention. Finally, text analysis results are compared with previous researches based on survey with limited questions and answers. This study is meaningful to expand the scope of employee discontent analysis with company review text and provide more specific, granular and honest discontent vocabularies.

• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.163-170
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• 2021

Smart-textronics technology which enables functional textiles has recently been applied in various fields such as smart clothes, smart home and smart health care, and a variety of smart-textronics products have been developed. In this context, the smart-textronics product development process is proposed based on the systematic participatory design method in this paper. The proposed method consists of two phases: in-depth interviews and analyzing. In the phase of in-depth interviews, participants are asked to create journey maps that include activities, pain points and emotional status and to generate solution ideas with sketches and simple prototypes. In the analyzing phase, design researchers investigate the participants' journey maps, and create personas by identifying critical characteristics with the behavior pattern analysis. Then, each persona's needs are linked with value elements of the E3 value framework. Finally, pre-survey was conducted to identify smart-textronics market and a smart sofa design is proceeded as the case study to show the applicability of the proposed method.

• Journal of Korean Society of Archives and Records Management
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• v.22 no.2
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• pp.117-133
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• 2022

The archival content listed arbitrarily makes it difficult for users to efficiently access the records of major economic policies, especially given that they use it without understanding the required period and context. Using the text mining techniques in the 30-year economic policy direction from 1991 to 2021, this paper derives economic-related keywords and changes that the government mainly dealt with. It collects and preprocesses major economic policies' background, main content, and body text and conducts text frequency, term frequency-inverse document frequency (TF-IDF), network, and time series analyses. Based on these analyses, the following words are recorded in order of frequency: "job(일자리)," "competitive(경쟁력)," and "restructuring(구조조정)." In addition, the relative ratio of "job (일자리)," "real estate(부동산)," and "corporation(기업)," by year was analyzed in terms of chronological order while presenting major keywords mentioned by each government. Based on the results, this study presents implications for developing and broadening the area of archival information services related to economic policies.

• Journal of the Korean Society for information Management
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• v.33 no.3
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• pp.155-176
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• 2016

This study aims to develope a scholarly metadata information system based on conceptual elements of text structure of Korean studies research articles and to identify the applicability of text structure based metadata as compared with the existing similar system. For the study, we constructed a database(Korean Studies Metadata Database, KMD) with text structure based on metadata of Korean Studies journal articles selected from the Korea Citation Index(KCI). Then we verified differences between KCI system and KMD system through search results using same keywords. As a result, KMD system shows the search results which meet the users' intention of searching more efficiently in comparison with the KCI system. In other words, even if keyword combinations and conditional expressions of searching execution are same, KMD system can directly present the content of research purposes, research data, and spatial-temporal contexts of research et cetera as search results through the search procedure.

• Journal of Digital Convergence
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• v.17 no.4
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• pp.211-217
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• 2019

As the widespread use of mobile health intervention among Korean patients with chronic disease, it is needed to identify research trends in mobile health intervention on chronic care using text mining technique. This secondary data analysis was conducted to investigate characteristics and main research topics in intervention studies from 2005 to 2018 with a total of 20 peer reviewed articles. Microsoft Excel and Text Analyzer were used for data analysis. Mobile health interventions were mainly applied to hypertension, diabetes, stroke, and coronary artery disease. The most common type of intervention was to develop mobile application. Lately, 'feasibility', 'mobile health', and 'outcome measure' were frequently presented. Future larger studies are needed to identify the relationships among key terms and the effectiveness of mobile health intervention using social network analysis.