• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.1085-1089
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• 2015

Text-mining technique in the past had difficulty in realizing the analysis algorithm due to text complexity and degree of freedom that variables in the text have. Although the algorithm demanded lots of effort to get meaningful result, mechanical text analysis took more time than human text analysis. However, along with the development of hardware and analysis algorithm, big data technology has appeared. Thanks to big data technology, all the previously mentioned problems have been solved while analysis through text-mining is recognized to be valuable as well. However, applying text-mining to Korean text is still at the initial stage due to the linguistic domain characteristics that the Korean language has. If not only the data searching but also the analysis through text-mining is possible, saving the cost of human and material resources required for text analysis will lead efficient resource utilization in numerous public work fields. Thus, in this paper, we compare and evaluate the public document classification by handwork to public document classification where word frequency(TF-IDF) in a text-mining-based text and Cosine similarity between each document have been utilized in big data environment.

• Geomechanics and Engineering
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• v.18 no.2
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• pp.111-119
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• 2019

Due to certain geological characteristics (high thickness, rocky properties), some underground coal mines require the use of explosives. This paper explores the effects of fragmentation of different decks detonated simultaneously in a single borehole with the use of numerical analysis. ANSYS/LS-DYNA code was used for the implementation of the models. The models include an erosion criterion to simulate the cracks generated by the explosion. As expected, the near-borehole area was damaged by compression stresses, while far zones and the free surface of the boundary were subjected to tensile damage. With the increase of the number of decks in the borehole, different changes in the fracture pattern were observed, and the superposition effects of the stress wave became evident, affecting the fragmentation results. The superposition effect is more evident in close distances to the borehole, and its effect attenuates when the distance to the borehole increase.

• Journal of the Korean Dietetic Association
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• v.23 no.2
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• pp.192-201
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• 2017

This study compared the Center for Children's Foodservice Management in 2012, 2014, and 2016 using big data and opinion mining. The data on the Center for Children's Foodservice Management were collected from the portal site, Naver, from January 1 to December 31 in 2012, 2014, & 2016 and analyzed by keyword frequency analysis, influx route analysis of data, polarity analysis via opinion mining, and positive and negative keyword analysis by polarity analysis. The results showed that nursery had the highest rank every year and education supported by Center for Children's Foodservice Management has increased significantly. The influx of data has increased through the influx route analysis of data. Blog and $caf\acute{e}e$, which have a considerable amount of information by the mother should be helpful for use as public relations and participation recruitment paths. By polarity analysis using opinion mining, the positive image of the Center for Children's Foodservice Management was increased. Therefore, the Center for Children's Foodservice Management was well-suited to the purpose and the interests of the people has been increasing steadily. In the near future, the Center for Children's Foodservice Management is expected have good recognition if various programs to participate with family are developed and advertised.

• Journal of the Korean Data and Information Science Society
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• v.16 no.3
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• pp.515-527
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• 2005

The data mining is a new approach to extract useful information through effective analysis of huge data in numerous fields. We utilized this data mining technique to analyze medical record of 39,900 people. Whole data were separated by gender first and divided into three groups, including normal, stage 1 hypertension, and stage 2 hypertension. The data from each group were analyzed with data mining technique. Based on the result that we have extracted with this data mining technique, major risk factors for the hypertension are age, BMI score, family history.

• ETRI Journal
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• v.33 no.5
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• pp.720-730
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• 2011

Opinion mining involves the analysis of customer opinions using product reviews and provides meaningful information including the polarity of the opinions. In opinion mining, feature extraction is important since the customers do not normally express their product opinions holistically but separately according to its individual features. However, previous research on feature-based opinion mining has not had good results due to drawbacks, such as selecting a feature considering only syntactical grammar information or treating features with similar meanings as different. To solve these problems, this paper proposes an enhanced feature extraction and refinement method called FEROM that effectively extracts correct features from review data by exploiting both grammatical properties and semantic characteristics of feature words and refines the features by recognizing and merging similar ones. A series of experiments performed on actual online review data demonstrated that FEROM is highly effective at extracting and refining features for analyzing customer review data and eventually contributes to accurate and functional opinion mining.

• Analytical Science and Technology
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• v.7 no.4
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• pp.477-482
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• 1994

By the instrumental neutron activation analysis using two comparators of gold and cobalt, 31 elements have been anlalyzed in anthracites collected from two main coal-fields in Korea. The average concentrations and ranges of the elements were obtained with the elemental difference between two coal-fields. The trends of rare-earth elemental distribution and vertical elemental distribution are also given.

• Journal of Korean Society for Atmospheric Environment
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• v.10 no.2
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• pp.90-97
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• 1994

PIXE( Proton Induced X- ray Emission ) analysis has been applied to the analysis of aerosol for the Purpose of pollution monitoring. Coarse and fine Particle fractions were sampled selectively, using Nuclepore filter in stacked filter units, once a month from February to September in 1993 at urban and rural sites. Concentration of 9 elements, Si, S, K, Ca, Mn, Fe, Cu, Zn and Pb was determined without Pretreatment of Samples. Comparison of data between urban and rural site revealed higher elemental concentration level in urban aerosol. From April to May aerosol sampling was carried out daily to observe the effect of Yellow Sand on the composition of aerosol in the Korean Peninsula. During the Yellow Sand period, Si, Ca, Fe content level in aerosol became more than 5 times higher than normal. The elemental concentration of the aerosol samples of Daejeon City was compared with that of two foreign cities. S and Pb( which are fuel- derived elements) levels in Daejeon City aerosol appeared to be lower than those of foreign cities. And it may be due to the leaded-fuel restriction policy of Korean government since 1987.

• Journal of the Korea Society of Computer and Information
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• v.24 no.7
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• pp.125-133
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• 2019

Because military weapons systems for special purposes are small and complex, they are not easy to maintain. Therefore, it is very important to maintain combat strength through quick maintenance in the event of a breakdown. In particular, naval ships are complex weapon systems equipped with various equipment, so other equipment must be considered for maintenance in the event of equipment failure, so that skilled maintenance personnel have a great influence on rapid maintenance. Therefore, in this paper, we analyzed maintenance data of defense equipment maintenance information system through text mining and social network analysis(SNA), and tried to identify the naval ship maintenance expertise. The defense equipment maintenance information system is a system that manages military equipment efficiently. In this study, the data(2,538cases) of some naval ship maintenance teams were analyzed. In detail, we examined the contents of main maintenance and maintenance personnel through text mining(word cloud, word network). Next, social network analysis(collaboration analysis, centrality analysis) was used to confirm the collaboration relationship between maintenance personnel and maintenance expertise. Finally, we compare the results of text mining and social network analysis(SNA) to find out appropriate methods for finding and finding naval ship maintenance expertise.

• Korea Trade Review
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• v.46 no.5
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• pp.65-81
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• 2021

The technological development in the era of the 4th industrial revolution is changing the paradigm of various industries. Various technologies such as big data, cloud, artificial intelligence, virtual reality, and the Internet of Things are used, creating synergy effects with existing industries, creating radical development and value creation. Among them, the logistics sector has been greatly influenced by quantitative data from the past and has been continuously accumulating and managing data, so it is highly likely to be linked with big data analysis and has a high utilization effect. The modern advanced technology has developed together with the data mining technology to discover hidden patterns and new correlations in such big data, and through this, meaningful results are being derived. Therefore, data mining occupies an important part in big data analysis, and this study tried to analyze data mining techniques that can contribute to the logistics field and common logistics using these data mining technologies. Therefore, by using the AHP technique, it was attempted to derive priorities for each type of efficient data mining for logisticalization, and R program and R Studio were used as tools to analyze this. Criteria of AHP method set association analysis, cluster analysis, decision tree method, artificial neural network method, web mining, and opinion mining. For the alternatives, common transport and delivery, common logistics center, common logistics information system, and common logistics partnership were set as factors.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.11-19
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• 2022

Data mining has broad applications that reach beyond scholarly and scientific research and provide internet search engine services that are commonly used forms of Text and Data Mining('TDM') of websites. The exceptions and limitations for data mining provide a competitive advantage in the global race for policy innovation because it permits researchers to conduct computational analysis - TDM on any materials to which they have access. For this purpose, Japan and the EU added limitations on copyright to legalize some TDM research through amendments to copyright law, and the U.S. copyright law has allowed data mining by the fair use provision. On the other hand, there are no explicit exceptions and limitations for data mining under the Korean Copyright Act, and there are no cases considering data mining fair use. We review comparatively exceptions and limitations on copyright which will help to encourage AI-related business by using more data smoothly through the mining process and extracting more valuable information.