• Journal of the Korea Convergence Society
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• v.10 no.10
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• pp.153-160
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• 2019

In this study, The purpose of this study is to analyze how the rating scale and review contents attributes of social network-based services and products affect consumer purchasing patterns. information provided by screening the main factors. These analyzes are closely and quickly integrated between individuals and businesses, and enable to analyze the transaction that the impact of changing consumers on consumption and purchasing through the usefulness and a priori estimates of reviews and ratings at this time when networks and smart technologies are involved in a wide range of consumer activities. For this study, hierarchical analysis (AHP) and delphi (Delphi) methods applied to classify the high end variables into usefulness, technicality and value, Each subvariable was grouped into three factors and analyzed for importance through evaluation weights. As a result, we could analyze the importance of durability, usefulness, technological innovation, and cost and quality of value. Therefore, this study is expected to provide supplementary and additional useful information to consumers and companies participating in economic activities in various ways by simultaneously analyzing the review score and the reliability of posting information provided by verifying the main factors.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.6
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• pp.7-17
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• 2009

The precise analysis of exercise data for designing an effective rehabilitation system is very important as a feedback for planing the next exercising step. Many subjective and reliable research outcomes that were obtained by analysis and evaluation for the human motor ability by various methods of biomechanical experiments have been introduced. Most of them include quantitative analysis based on basic statistical methods, which are not practical enough for application to real clinical problems. In this situation, data mining technology can be a promising approach for clinical decision support system by discovering meaningful hidden rules and patterns from large volume of data obtained from the problem domain. In this research, in order to find relational rules between posture training type and muscle activation pattern, we investigated an application of the WAR(Weishted Association Rule) to the biomechanical data obtained mainly for evaluation of postural control ability. The discovered rules can be used as a quantitative prior knowledge for expert's decision making for rehabilitation plan. The discovered rules can be used as a more qualitative and useful priori knowledge for the rehabilitation and clinical expert's decision-making, and as a index for planning an optimal rehabilitation exercise model for a patient.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.6 no.3
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• pp.1-11
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• 2007

Seoul's transportation system was changed drastically starting the first of June in two thousand. This policy includes integrated distance-based fare system and public transportation card system called smart card. Especially, as public transportation card data contains individual travel, transfer and using modes information it is possible to catch the characteristics of path-based individuals and mass transit. Thus, public transportation card data can contribute to evaluate the mass transit service in integrated public transportation networks. In addition, public transportation card data are able to help to convert previous researches and analyses with link-based trip assignment models to path-based mass transit service analysis. In this study, an algorithm being suitable for path-based trip assignment models is suggested and proposed algorithm can also contribute to make full use of public transportation card data. For this, column generation algorithm hewn to draw the stable solution is adopted. This paper uses the methodology that is to take local approximate equilibrium from partial network and expand local approximate equilibrium to global equilibrium.

• The korean journal of orthodontics
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• v.33 no.6 s.101
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• pp.407-418
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• 2003

The purpose of this study is to analyze dentoalveolar compensation in normal occlusion samples previously classified into 9 skeletal types, and to provide clinically applicable diagnostic criteria for individual malocclusion patients. Cephalometric measurements of the 294 normal occlusion samples previously divided into 9 types were analyzed. The descriptive features of dentoalveolar variables were compared for the 9 types using analysis of variance, followed by post hoc multiple comparisons. In addition, the correlation between skeletal and dentoalveolar variables were analyzed. Discriminant analysis with a stepwise entry of variables was designed to find out several potential variables for use in skeletal typing. The dentoalveolar compensation pattern of the skeletal types varied, especially with regards to the variables that indicated the inclination of incisors and the occlusal plane. Stepwise variable selection identified four variables: AB-MP, SN-AB, PMA and ANB. Discriminant analysis assigned a classification accuracy of $87.8\%$ to the predictive model. On the basis of these results, this study could provide rudimentary information for the development of diagnostic criteria and treatment guidelines for individual skeletal types.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.2
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• pp.28-37
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• 2011

With growing concerns about healthy life recently, although the podiatry which deals with the whole area for diagnosis, treatment of foot and leg, and prevention has been widely interested, research in our country is not active. Also, because most of the previous researches in data analysis performed the quantitative approaches, the reasonable level of reliability for clinical application could not be guaranteed. Clinical data mining utilizes various data mining analysis methods for clinical data, which provides decision support for expert's diagnosis and treatment for the patients. Because the decision tree can provide good explanation and description for the analysis procedure and is easy to interpret the results, it is simple to apply for clinical problems. This study investigate rules of item of diagnosis in disease types for adapting decision tree after collecting diagnosed data patients who are 2620 feet of 1310(males:633, females:677) in shoes clinic (department of rehabilitation medicine, Chungnam National University Hospital). and we classified 15 foot diseases followed factor of 22 foot diseases, which investigated diagnosis of 64 rules. Also, we analyzed and compared correlation relationship of characteristic of disease and factor in types through made decision tree from 5 class types(infants, child, adolescent, adult, total). Investigated results can be used qualitative and useful knowledge for clinical expert`s, also can be used tool for taking effective and accurate diagnosis.

• Spatial Information Research
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• v.21 no.2
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• pp.55-71
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• 2013

This study assessed the thermal comfort of new towns in the Seoul Metropolitan Area (Ilsan, Bundang, Dongtan1) using PET (Physiologically Equivalent Temperature) which refers to real human heat stress. The relationship between PET and urban spatial elements was also analyzed using multiple regression analysis. The study results show that the thermal comfort of Dongtan 1, which is considering a reduction of the urban heat island effect in the planning phase, is higher than other cities. In addition, through regression results, the impervious ratio, floor area ratio, commercial area ratio, and residential area ratio were found to be major factors increasing PET. Moreover, the river area ratio and NDVI were found to be major factors decreasing PET. This study has scientific significance as research that focuses on the assessment of thermal comfort scientifically and definitely, by estimating PET for an entire urban area using GIS analysis that included remote sense analysis and the wind field model. The results of this study can be used in preparing more effective urban plans for the promotion of citizen thermal comfort.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.12
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• pp.2357-2364
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• 2008

In this paper, we consider the problem of exploiting a taxonomy of propositionalized attributes in order to generate compact and robust classifiers. We introduce Propositionalized Attribute Taxonomy guided Naive Bayes Learner (PAT-NBL), an inductive learning algorithm that exploits a taxonomy of propositionalized attributes as prior knowledge to generate compact and accurate classifiers. PAT-NBL uses top-down and bottom-up search to find a locally optimal cut that corresponds to the instance space from propositionalized attribute taxonomy and data. Our experimental results on University of California-Irvine (UCI) repository data set, show that the proposed algorithm can generate a classifier that is sometimes comparably compact and accurate to those produced by standard Naive Bayes learners.

• Proceedings of the Korean DIstribution Association Conference
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• 2006.08a
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• pp.47-68
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• 2006

This study aims to determine the association structure of the behavioral relationship variables, such as trust, commitment, cooperation, communication and coercive power, in the relationship between the buyers and suppliers of industrial parts. It also investigates the impact of the use of IT technologies on the relationships quality. Data was collected from 216 part suppliers of machinery, electronics and automobiles located in Incheon. Data supported all of the proposed hypotheses. First, it was confirmed that parts suppliers' trust in buyers leads to the commitment into relationships with buyers. Second, cooperation and communication showed a positive influence on parts suppliers' trust in buyers, and coercive power gave a negative influence on trust. Third, the use of IT technologies like Internet and E-Mail between parts suppliers and buyers was verified to have generally a positive influence on the quality of relationships. At the same time, cooperation and communication were confirmed to have a positive influence on each other, and cooperation and coercive power as well as communication and coercive power were confirmed to have negative influence on each other. This study is a pioneering attempt to examine the relationships between suppliers and buyers of industrial parts, and the influence IT technologies on the relationship quality. Also, the findings will be practically much helpful to find how to reinforce the relationships between parts suppliers and buyers.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.406-409
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• 2008

We consider the problem of exploiting a taxonomy of propositionalized attributes in order to learn compact and robust classifiers. We introduce Propositionalized Attribute Taxonomy guided Naive Bayes Learner (PAT-NBL), an inductive learning algorithm that exploits a taxonomy of propositionalized attributes as prior knowledge to generate compact and accurate classifiers. PAT-NBL uses top-down and bottom-up search to find a locally optimal cut that corresponds to the instance space from propositionalized attribute taxonomy and data. Our experimental results on University of California-Irvine (UCI) repository data sets show that the proposed algorithm can generate a classifier that is sometimes comparably compact and accurate to those produced by standard Naive Bayes learners.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.2
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• pp.111-118
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• 2015

Entity linking is to link entity's name mentions occurring in text to corresponding entities within knowledge bases. Since the same entity mention may refer to different entities according to their context, entity linking needs to deal with entity disambiguation. Most recent works on entity disambiguation focus on semantic relatedness between entities and attempt to integrate semantic relatedness with entity prior probabilities and term co-occurrence. To the best of my knowledge, however, it is hard to find studies that analyze and present the pure effects of semantic relatedness on entity disambiguation. From the experimentation on Korean Wikipedia data set, this article empirically evaluates entity disambiguation approaches using semantic relatedness in terms of the following aspects: (1) the difference among semantic relatedness measures such as NGD, PMI, Jaccard, Dice, Simpson, (2) the influence of ambiguities in co-occurring entity mentions' set, and (3) the difference between individual and collective disambiguation approaches.