• The Journal of the Korea Contents Association
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• v.20 no.2
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• pp.96-104
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• 2020

As consumers' consumption activities become more active due to the activation of online shopping malls, companies are conducting item trend analyses to boost sales. The existing item trend analysis methods are analyzed by considering only the activities of users in online shopping mall services, making it difficult to identify trends for new items without purchasing history. In this paper, we propose a trend analysis method that combines data in online shopping mall services and social network data to analyze item trends in users and potential customers in shopping malls. The proposed method uses the user's activity logs for in-service data and utilizes hot topics through word set extraction from social network data set to reflect potential users' interests. Finally, the item trend change is detected over time by utilizing the item index and the number of mentions in the social network. We show the superiority of the proposed method through performance evaluations using social network data.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.384-399
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• 2021

This study aims to identify the characteristics and meanings that Korean musical enthusiasts take on as cultural intermediaries of musical content by analyzing the real-time conversations they have while watching musicals performed in online spaces. To this end, the 'Live TALK' chat during the 'ontact' (online contact) performance of the musical Marie Curie was observed in real-time and subsequently analyzed in terms of the characteristics of online cultural intermediaries: their owned capital, their mediating language, and their relationship with the consumers. As a result of the analysis, musical enthusiasts were found to possess a wealth of cultural capital based on practical experience and inquiry, and to be utilizing specific identifying expressions in their language use. In addition, they appeared to be interactive in their communication with the general audience, which could be seen in the flow of spontaneous conversations as well as questions and answers occurring in the live chat. This study is significant in confirming that musical enthusiasts are positioning themselves as new cultural intermediaries through their cultural practices: taking on the role of guides and mediators in the online space 'Live TALK.'

• Fashion & Textile Research Journal
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• v.25 no.2
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• pp.165-174
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• 2023

This study analyzed the purchase status of athleisure wear and consumers' dissatisfaction with online shopping post-COVID-19. The target population comprised female consumers in their 20s to 50s who are interested in exercise and fashion. The study investigated differences according to age. It was found that athleisure wear was purchased once every two to three months and used as sportswear and/or daily wear. Purchase information was obtained via the Internet, and purchases were made online. Design, price, wear sensation, and textiles were the most important selection criteria, and T-shirts and leggings were the most frequently purchased garments. Additionally, textile characteristics such as moisture-absorbing and quick-drying as well as elasticity were evaluated as important. Online shopping of athleisure wear has increased since COVID-19 due to the time savings, low price, opportunity to compare several products, and delivery convenience. However, consumers were dissatisfied due to the differences between the screen image and the actual product, the inconvenience of returns, exchanges, and refunds, the lack of product information, product quality, and delivery. Furthermore, it was found that pursuing value of athleisure wear differed according to age. Consumers in their 20s and 30s required athleisure wear with the characteristics of sportswear and daily or urban wear and those in their 40s and 50s required garments with good performance as sportswear. Based on consumer feedback, it is necessary for manufacturers to provide product information that can improve product reliability.

• Journal of the Korea Society of Computer and Information
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• v.29 no.6
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• pp.193-200
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• 2024

This study aims to answer the following questions: 'Do university students who are satisfied with their online courses have higher academic achievement?' and 'What are the key self-regulated learning strategy factors that influence satisfaction and academic performance?'. To do this, this study conducted a survey of university students taking online courses and collected a total of 95 questionnaires. Research method used structural equation model. The results of the analysis showed that, First, satisfaction and academic achievement in university online courses were found to be unrelated. Second, the factors affecting satisfaction and academic achievement were found to be different. Time management was analyzed as a significant factor affecting both satisfaction and academic achievement, while interaction was found to affect satisfaction only. These findings can be used as a basis for developing practical policies to prioritize and support self-regulated learning as an effective teaching method in university online courses.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2012.05a
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• pp.586-591
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• 2012

The solution of maintenance decision support system for the gas turbine engine, which is currently operating in GUNSAN combined cycle power plant, was developed and is consist of online monitoring module, periodic performance trending module, optimal compressor washing interval analysis module and hot component management module. Also, GUI platform was applied to this solution for the user to monitoring the analyzed result of engine performance condition and then to make a decision of the consequent maintenance action. In online condition monitoring module, the performance degradation of engine is provided by the analysis of difference between the real time measurement data compared to exist engine performance. The optimal compressor washing interval module produced the washing interval of maximum net profit value by researching the maintenance expense and the loss profit value corresponds to the performance degradation with economic assessment algorithm. Thus, this solution support the user to enable the optimal maintenance and operation of gas turbine engine with overall analysis of engine condition and main information.

• Journal of Digital Convergence
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• v.15 no.8
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• pp.103-114
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• 2017

With the development of IT technology and the establishment of logistics infrastructure, online shopping market and online fresh food market are growing. The purpose of this study is to find a plan to activate Fresh Logistics through online shopping mall using BCG matrix and Importance Performance Analysis for online shopping companies. Firstly, the BCG matrix results Companies in 'cash cow', 'question mark', and 'dog' areas are in need of improvement. In order to improve this situation, it is necessary to activate the Fresh logistics market which is currently growing. Fresh logistics can be activated by investing in the maintenance and strengthening areas and key investment areas by minimizing the expenditure on the non-priority and excess areas according to the results of IPA. Therefore, it is expected that online shopping companies will be improved by activating online shopping market and online fresh logistics market.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.12
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• pp.533-540
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• 2013

Anonymity is the one of main reasons for substantial improvement of Internet. It encourages various users to express their opinion freely and helps Internet based distributed systems vitalize. But, anonymity can cause unexpected threats because personal information of an online user is hidden. Especially, distributed systems are threatened by Sybil attack, where one malicious user creates and manages multiple fake online identities. To prevent Sybil attack, the traditional solutions include increasing the complexity of identity generation and mapping online identities to real-world identities. But, even though the high complexity of identity generation increases the generation cost of Sybil identities, eventually they are generated and there is no further way to suppress their activity. Also, the mapping between online identities and real identities may cause high possibility of losing anonymity. Recently, some methods using online social network to prevent Sybil attack are researched. In this paper, a new method is proposed for extracting a user's system-wide Sybil-resistant trust value by using the properties embedded in online social network graphs. The proposed method can be categorized into 3 types based on sampling and decision strategies. By using graphs sampled from Facebook, the performance of the 3 types of the proposed method is evaluated. Moreover, the impact of Sybil attack on nodes with different characteristics is evaluated in order to understand the behavior of Sybil attack.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.5
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• pp.189-196
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• 2022

Skyline query is a scheme for exploring objects that are suitable for user preferences based on multiple attributes of objects. Existing skyline queries return search results as batch processing, but the need for real-time search results has increased with the advent of interactive apps or mobile environments. Online algorithm for Skyline improves the return speed of objects to explore preferred objects in real time. However, the object navigation process requires unnecessary navigation time due to repeated comparative operations. This paper proposes a Pre-processing Online Algorithm for Skyline Query (POA) to eliminate unnecessary search time in Online Algorithm exploration techniques and provide the results of skyline queries in real time. Proposed techniques use the concept of range-limiting to existing Online Algorithm to perform pretreatment and then eliminate repetitive rediscovering regions first. POAs showed improvement in standard distributions, bias distributions, positive correlations, and negative correlations of discrete data sets compared to Online Algorithm. The POAs used in this paper improve navigation performance by minimizing comparison targets for Online Algorithm, which will be a new criterion for rapid service to users in the face of increasing use of mobile devices.

• Korean Journal of Culture and Social Issue
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• v.28 no.4
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• pp.661-690
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• 2022

Adolescent delinquency is a substantial social problem that occurs in both offline and online domains. The current study utilized random forest algorithms to identify predictors of adolescents' online and offline delinquency. Further, we explored the applicability of classic delinquency theories (social learning, strain, social control, routine activities, and labeling theory). We used the first-grade and fourth-grade elementary school panels as well as the first-grade middle school panel (N=4,137) among the sixth wave of the nationally-representative Korean Children and Youth Panel Survey 2010 for analysis. Random forest algorithms were used instead of the conventional regression analysis to improve the predictive performance of the model and possibly consider many predictors in the model. Random forest algorithm results showed that classic delinquency theories designed to explain offline delinquency were also applicable to online delinquency. Specifically, salient predictors of online delinquency were closely related to individual factors(routine activities and labeling theory). Social factors(social control and social learning theory) were particularly important for understanding offline delinquency. General strain theory was the commonly important theoretical framework that predicted both offline and online delinquency. Findings may provide evidence for more tailored prevention and intervention strategies against offline and online adolescent delinquency.

• Asia pacific journal of information systems
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• v.28 no.3
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• pp.167-182
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• 2018

The purpose of this study is to investigate the relationship between knowledge sharing and academic performance in the context of quality-assurance related work. It furthermore aims to explore the role of information technology in mediating this relationship. Quantitative method was applied to collect data from the participants using an online-based questionnaire. Convenience sampling technique was used. The responses were collected from 140 participants in a university from Saudi Arabia. The study found a strong positive relationship between knowledge sharing and individual performance. It was also found out that information technology partially mediates the relationship between knowledge sharing and individual performance. The research unearths the significant contribution made by information technology in mediating the relationship between individual-level knowledge sharing and the individual performance. This helps to understand the positive impacts on individual work performance in institutions of higher education that would be derived if individuals use various forms of IT to share knowledge. The focus of the research is the individual performance as the pertinent contribution towards positive outcomes in institutional performance.