• 제목/요약/키워드: Role Mining

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Bridge-edges Mining in Complex Power Optical Cable Network based on Minimum Connected Chain Attenuation Topological Potential

  • Jiang, Wanchang;Liu, Yanhui;Wang, Shengda;Guo, Jian
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.3
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    • pp.1030-1050
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    • 2021
  • The edges with "bridge characteristic" play the role of connecting the communication between regions in power optical cable network. To solve the problem of mining edges with "bridge characteristic" in provincial power optical cable network, the complex power optical cable network model is constructed. Firstly, to measure the generated potential energy of all nodes in n-level neighborhood local structure for one edge, the n-level neighborhood local structure topological potential is designed. And the minimum connected chain attenuation is designed to measure the attenuation degree caused by substituted edges. On the basis of that, the minimum connected chain attenuation topological potential based measurement is designed. By using the designed measurement, a bridge-edges mining algorithm is proposed to mine edges with "bridge characteristic". The experiments are conducted on the physical topology of the power optical cable network in Jilin Province. Compared with that of other three typical methods, the network efficiency and connectivity of the proposed method are decreased by 3.58% and 28.79% on average respectively. And the proposed method can not only mine optical cable connection with typical "bridge characteristic" but also can mine optical cables without obvious characteristics of city or voltage, but it have "bridge characteristic" in the topology structure.

Text-mining based Cause Analysis of Accidents at Workplaces in Korea (텍스트 마이닝 기법을 활용한 우리나라 산업재해의 원인분석)

  • Choi, Gi Heung
    • Journal of the Korean Society of Safety
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    • v.37 no.3
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    • pp.9-15
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    • 2022
  • The analysis of the causes of accidents in workplaces where machines and tools are used is essential to improve the effectiveness and efficiency of safety prevention policies in places of employment in Korea. The causes of workplace accidents are not fully understood mainly due to difficulties in analyzing available descriptive information. This study focuses on the automated accident cause analysis in workplaces based on the accident abstracts found in industrial accident reports written in an unstructured descriptive format. The method proposed in this paper is based on text data mining and uses the keyword search function of Excel software to automate the analysis. The analysis results indicate that the primary reason for the frequency of accidents is related to technical aspects at a stage in which dangerous situations occur in the workplace. Accidents due to managerial causes are typically observed when danger exists in the workplace; however, managerial actions play a more important role in reducing accident severity. A small company tends to use unsafe machines and devices, leading to further accidents due to technical causes, whereas managerial causes are more conspicuous as the company grows. To preclude the occurrence of accidents due to inadequate knowledge, the implementation of safety management and the provision of safety education to elderly workers at the early stage of their employment are particularly important for small companies with less than 100 workers.

The Impact of Product Review Usefulness on the Digital Market Consumers Distribution

  • Seung-Yong LEE;Seung-wha (Andy) CHUNG;Sun-Ju PARK
    • Journal of Distribution Science
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    • v.22 no.3
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    • pp.113-124
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    • 2024
  • Purpose: This study is a quantitative study and analyzes the effect of evaluating the extreme and usefulness of product reviews on sales performance by using text mining techniques based on product review big data. We investigate whether the perceived helpfulness of product reviews serves as a mediating factor in the impact of product review extremity on sales performance. Research design, data and methodology: The analysis emphasizes customer interaction factors associated with both product review helpfulness and sales performance. Out of the 8.26 million Amazon product reviews in the book category collected by He & McAuley (2016), text mining using natural language processing methodology was performed on 300,000 product reviews, and the hypothesis was verified through hierarchical regression analysis. Results: The extremity of product reviews exhibited a negative impact on the evaluation of helpfulness. And the helpfulness played a mediating role between the extremity of product reviews and sales performance. Conclusion: Increased inclusion of extreme content in the product review's text correlates with a diminished evaluation of helpfulness. The evaluation of helpfulness exerts a negative mediating effect on sales performance. This study offers empirical insights for digital market distributors and sellers, contributing to the research field related to product reviews based on review ratings.

Analysis of stress distribution around tunnels by hybridized FSM and DDM considering the influences of joints parameters

  • Nikadat, Nooraddin;Marji, Mohammad Fatehi
    • Geomechanics and Engineering
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    • v.11 no.2
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    • pp.269-288
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    • 2016
  • The jointed rock mass behavior often plays a major role in the design of underground excavation, and their failures during excavation and in operation, are usually closely related to joints. This research attempts to evaluate the effects of two basic geometric factors influencing tunnel behavior in a jointed rock mass; joints spacing and joints orientation. A hybridized indirect boundary element code known as TFSDDM (Two-dimensional Fictitious Stress Displacement Discontinuity Method) is used to study the stress distribution around the tunnels excavated in jointed rock masses. This numerical analysis revealed that both the dip angle and spacing of joints have important influences on stress distribution on tunnel walls. For example the tensile and compressive tangential stresses at the boundary of the circular tunnel increase by reduction in the joint spacing, and by increase the dip joint angle the tensile stress in the tunnel roof decreases.

A Study on Agile Transformation in the New Digital Age

  • Lee, Jee Young
    • International Journal of Advanced Culture Technology
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    • v.8 no.1
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    • pp.82-88
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    • 2020
  • In the face of recent digital and digital transformation, companies and industries are trying to be agile to adapt and respond to change. Agile paradigm is spreading beyond the boundaries of existing applications such as IT-related projects and software development. In this regard, this study, we analyzed the diffusion of agile paradigm by text mining abstracts of research papers from 2001 to 2019. In addition, we discussed agile transformation in the Fourth Industrial Revolution. Through this study, we confirmed that we are studying agile transformation in various fields such as business environment, corporate organizational culture, manufacturing industry, and supply chain. The results of this study will contribute to understanding the meaning and role of agile as a basic paradigm for digital transformation in the Fourth Industrial Revolution.

Prediction of the mechanical properties of granites under tension using DM techniques

  • Martins, Francisco F.;Vasconcelos, Graca;Miranda, Tiago
    • Geomechanics and Engineering
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    • v.15 no.1
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    • pp.631-643
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    • 2018
  • The estimation of the strength and other mechanical parameters characterizing the tensile behavior of granites can play an important role in civil engineering tasks such as design, construction, rehabilitation and repair of existing structures. The purpose of this paper is to apply data mining techniques, such as multiple regression (MR), artificial neural networks (ANN) and support vector machines (SVM) to estimate the mechanical properties of granites. In a first phase, the mechanical parameters defining the complete tensile behavior are estimated based on the tensile strength. In a second phase, the estimation of the mechanical properties is carried out from different combination of the physical properties (ultrasonic pulse velocity, porosity and density). It was observed that the estimation of the mechanical properties can be optimized by combining different physical properties. Besides, it was seen that artificial neural networks and support vector machines performed better than multiple regression model.

The impact of sidetracking on the wellbore stability

  • Elyasi, Ayub;Goshtasbi, Kamran
    • Advances in Energy Research
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    • v.3 no.1
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    • pp.1-10
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    • 2015
  • In the past sidetracking was the means to bypass a damaged zone or to correct the direction of a wellbore. Nowadays, this method is very common and useful in relocating the bottom of a wellbore in a more productive zone and consequently enhancing the production of a reservoir by saving a significant amount of time and money. In this paper, the stability of the bend area is assessed considering varied conditions of stress regime and sidetrack orientation. In general, the stress regime and the orientation of the principal stresses have negligible effect on the stability of the sidetrack compared to sidetrack inclination. On the other hand, the sidetrack deviation angle from the vertical main well plays the major role in the stability of the bend area.

Political Opinion Mining from Article Comments using Deep Learning

  • Sung, Dae-Kyung;Jeong, Young-Seob
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.1
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    • pp.9-15
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    • 2018
  • Policy polls, which investigate the degree of support that the policy has for policy implementation, play an important role in making decisions. As the number of Internet users increases, the public is actively commenting on their policy news stories. Current policy polls tend to rely heavily on phone and offline surveys. Collecting and analyzing policy articles is useful in policy surveys. In this study, we propose a method of analyzing comments using deep learning technology showing outstanding performance in various fields. In particular, we designed various models based on the recurrent neural network (RNN) which is suitable for sequential data and compared the performance with the support vector machine (SVM), which is a traditional machine learning model. For all test sets, the SVM model show an accuracy of 0.73 and the RNN model have an accuracy of 0.83.

A Study on the Integration Between Smart Mobility Technology and Information Communication Technology (ICT) Using Patent Analysis

  • Alkaabi, Khaled Sulaiman Khalfan Sulaiman;Yu, Jiwon
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.6
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    • pp.89-97
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    • 2019
  • This study proposes a method for investigating current patents related to information communication technology and smart mobility to provide insights into future technology trends. The method is based on text mining clustering analysis. The method consists of two stages, which are data preparation and clustering analysis, respectively. In the first stage, tokenizing, filtering, stemming, and feature selection are implemented to transform the data into a usable format (structured data) and to extract useful information for the next stage. In the second stage, the structured data is partitioned into groups. The K-medoids algorithm is selected over the K-means algorithm for this analysis owing to its advantages in dealing with noise and outliers. The results of the analysis indicate that most current patents focus mainly on smart connectivity and smart guide systems, which play a major role in the development of smart mobility.

Changes in Specialty Coffee Consumption Post-pandemic

  • Lim, Miri;Ryu, Gihwan
    • International journal of advanced smart convergence
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    • v.11 no.3
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    • pp.157-161
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    • 2022
  • The coffee industry continues to grow steadily due to the spread of coffee and changes in consumer awareness. Once upon a time, instant coffee was common, People today have distinct personal preferences As consumption needs for favorite foods are segmented, ways to enjoy coffee are diversifying. This study was conducted through analysis of consumption changes for specialty coffee as a changed issue of COVID-19 The goal is to present a vision for the future of the specialty coffee industry. As a research method, text mining through big data analysis was conducted to extract and analyze factors affecting the change in specialty coffee consumption. As a result of the study, we judged that specialty coffee is consumed by using a drip tool that allows you to easily enjoy coffee at home after Corona 19. Therefore, hand drips used in home cafes were found to play a central role in the change in specialty coffee consumption.