• Journal of the Korea Safety Management & Science
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• v.9 no.3
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• pp.135-142
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• 2007

The authors used association rules and patterns in sequential of data mining in order to raise the efficiency of engineering changes. The association rule can reduce the number of engineering changes since it can estimate the parts to be changed. The patterns in sequential can perform engineering changes effectively by estimating the parts to be changed from sequence estimation. According to this result, unnecessary engineering changes are eliminated and the number of engineering changes decrease. This method can be used for improving design quality and productivity in company managing engineering changes and related information.

• Journal of Korean Institute of Industrial Engineers
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• v.38 no.1
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• pp.67-73
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• 2012

Identification of meaningful patterns and trends in large volumes of text data is an important task in various research areas. In the present study we crawled the keywords from the abstracts in IIE Transactions, one of the representative journals in the field of Industrial Engineering from 1969 to 2011. We applied low-dimensional embedding method, clustering analysis, association rule, and social network analysis to find meaningful associative patterns of key words frequently appeared in the paper.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.01a
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• pp.281-282
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• 2014

병의원에서 다양한 정보시스템을 도입하면서 환자들과 관련된 방대한 의료 데이터들이 전자적인 형태로 축적되어 왔고, 최근에는 의료진이나 환자에게 적절한 정보를 제공하는데 이러한 데이터를 활용하고자 하는 노력이 이어지고 있다. 그러나 의료 데이터는 분량이 방대하고 전문적인 내용을 다루기 때문에 이에 기반한 정보를 개인 환자에게 제공하는데 있어서는 데이터에 포함된 내용을 사용자의 이해가 편리한 형태로 가공하는 것이 중요하다. 이에 본 논문에서는 연관분석과 관련된 행렬 기반 표현 방법을 기반으로 한 하이브리드 시각화 방법을 개발하고, 이를 건강검진 결과에 적용하는 것을 제안하고자 한다.

• Journal of the Korean Home Economics Association
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• v.47 no.5
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• pp.67-77
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• 2009

This study examined risk factors and protective factors in high school students’ suicidal ideation. Participants were 2000 adolescents from the KEEP(Korean Education and Employment Panel). Data mining decision tree model revealed that: (1) Irrespective of sex, the most important predictor was father-adolescent relationship. (2) Positive mother-adolescent relationship was predicted as protective factor in condition of negative father-adolescent relationship. (3) Family activities was predicted as risk factor in condition of negative mother-adolescent relationship under the circumstances with negative father-adolescent relationship. (4) Low self-evaluation was predicted as risk factor in condition of serious agony about personality under the circumstances with positive father-adolescent relationship.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.1
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• pp.52-59
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• 2014

We survey 3,857 journal articles published on the four domestic academic journals in the industrial engineering field during 1975~2012. Titles, abstracts, and keywords of the papers are searched by means of text mining technique to draw the information on the methodologies and techniques adopted in the papers, and then we aggregate and merge similar ones to obtain final 38 representative methodologies and techniques. Trends of these methodologies and techniques are studied by analyzing frequencies, clustering, and finding association rules among them. Results of the paper can shed a light to choose tools in the future education and research in the industrial engineering related area.

• Proceedings of the Korea Contents Association Conference
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• 2018.05a
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• pp.7-8
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• 2018

This study proposes an analysis of the Word2vec-based machine learning classifiers for the sake of opinion mining tasks. As a bench-marking method, BOW (Bag-of-Words) was adopted. On the basis of utilizing the Word2vec and BOW as feature extraction methods, we applied Laptop and Restaurant dataset to LR, DT, SVM, RF classifiers. The results showed that the Word2vec feature extraction yields more improved performance.

• Journal of Korean Association for Spatial Structures
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• v.21 no.3
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• pp.85-92
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• 2021

The purpose of this paper is to understand the key factors for efficient maintenance of rapidly aging facilities. Therefore, the safety inspection/diagnosis reports accumulated in the unstructured data were collected and preprocessed. Then, the analysis was performed using a text mining analysis method. The derived vulnerabilities of tunnel facilities can be used as elements of inspections that take into account the characteristics of individual facilities during regular inspections and daily inspections in the short term. In addition, if detailed specification information and other inspection results(safety, durability, and ease of use) are used for analysis, it provides a stepping stone for supporting preemptive maintenance decision-making in the long term.

• Asian Journal of Innovation and Policy
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• v.8 no.1
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• pp.73-96
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• 2019

This study suggests a new approach for identifying core robot tech-nologies based on technological cross-impact. Specifically, the approach applies data mining techniques and multi-criteria decision-making methods to the co-classification information of registered patents on the robots. First, a cross-impact matrix is constructed with the confidence values by applying association rule mining (ARM) to the co-classification information of patents. Analytic network process (ANP) is applied to the co-classification frequency matrix for deriving weights of each robot technology. Then, a technique for order performance by similarity to ideal solution (TOPSIS) is employed to the derived cross-impact matrix and weights for identifying core robot technologies from the overall cross-impact perspective. It is expected that the proposed approach could help robot technology managers to formulate strategy and policy for technology planning of robot area.

• Journal of the Korea Society for Simulation
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• v.11 no.4
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• pp.15-23
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• 2002

As recently the network environment and application services have been more complex and diverse, there has. In this paper we introduce a scheme the extract useful information for network management by analyzing traffic data in user login file. For this purpose we use classification and association rule based on episode concept in data mining. Since login data has inherently time series characterization, convertible data mining algorithms cannot directly applied. We generate virtual transaction, classify transactions above threshold value in time window, and simulate the classification algorithm.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.6
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• pp.63-71
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• 2011

The current Web portal sites provide significant keywords with high popularity or importance; specifically, user-friendly services such as tag clouds and associated word search are provided. However, in general, since news articles are classified only with their date and categories, it is not easy for users to find other articles related to some articles while reading news articles classified with categories. And the conventional associated keyword service has not satisfied users sufficiently because it depends only upon user queries. This paper proposes a way of searching news articles by utilizing the keywords tightly associated with users' queries. Basically, the proposed method discovers a set of keyword association patterns by using the association rule mining technique that extracts association patterns for keywords by focusing upon sentences containing some keywords. The method enables users to navigate the space of associated keywords hidden in large news articles.