• Journal of Distribution Science
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• v.22 no.9
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• pp.39-48
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• 2024

Purpose: The purpose of this study is to collect and analyze a large amount of data from online ticket distribution platforms that offer multiple airlines and different routes so that they can improve their ticket distribution marketing strategies and provide services that are more suitable for consumer's needs. The results of this study will help airlines improve the quality of their online platform services to provide more benefits and convenience by providing access to multiple airlines and routes around the world on one platform. Research design, data and methodology: For the study, 200 people completed the survey between May 1 and June 15, 2024, of which 191 copies were used in the study. Results: The hypothesis testing results of this study showed that among the components of the recommendation algorithm, decision comport, novelty, and evoked interest recurrence had a positive effect on perceived recommendation quality, but curiosity did not have a positive effect on recommendation quality. The perceived recommendation quality of the online platform positively influenced recommendation satisfaction, and the higher the perceived recommendation quality, the higher the intention to continue the relationship. Finally, higher recommendation satisfaction was associated with higher relationship continuation intention. Conclusion: it's important to continue researching online ticketing platforms. Online platforms will also need to be systems that use technology and data analytics to provide a better user experience and more benefits.

• Journal of Information Technology Services
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• v.11 no.sup
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• pp.139-152
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• 2012

In the medical web forum, people share medical experience and information as patients and patents' families. Some people search medical information written in non-expert language and some people offer words of comport to who are suffering from diseases. Medical web forums play a role of the informative support and the emotional support. We propose the automatic classification model of articles in the medical web forum into the information support and emotional support. We extract text features of articles in web forum using text mining techniques from the perspective of linguistics and then perform supervised learning to classify texts into the information support and the emotional support types. We adopt the Support Vector Machine (SVM), Naive-Bayesian, decision tree for automatic classification. We apply the proposed model to the HealthBoards forum, which is also one of the largest and most dynamic medical web forum.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.1905-1913
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• 2011

The dynamic characteristic of bogie that is driving system of railway vehicle is very important regarding decision of vehicle characteristics as running safety and comport. The dynamic characteristic test of bogie is tested on full size in place on field testing on track. But, the testing on the full size caused many problems. To overcome these problem by full size test, the Railway Safety Research Center in Seoul National University of Science & Technology developed 1/5 scale size of small scale derailment simulator and is currently testing running stability of 1/5 scaled bogie. Also To take effectively advantage of running stability test using small scale derailment simulator in actuality design and reliability estimation, it is necessary comparison and examination with field test and theoretical analysis result In this paper. to achieve running stability analysis of 1/5 scaled bogie on small scale derailment. the program using MATLAB that is fast compose and analysis the motion equation of Saemaul power bogie is developed. It is achieved analysis according to various specification (weight, size, suspension, etc..) and is evaluated corelation between test result and dynamic characteristic of actual railway vehicle.