• International journal of advanced smart convergence
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• v.11 no.2
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• pp.128-134
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• 2022

Nowadays, people consume a lot of content such as web dramas or K-pop videos through mobile devices such as smartphones, and the market for indirect advertisements through these web dramas or K-pop videos is also increasing every year. In order to lead to the immediate purchase of indirect products in web dramas, a system that allows consumers to purchase immediately at the time the products appear in the drama is needed. In this paper, we propose a system to allow viewers to purchase products worn by celebrities immediately when viewers see and click on them. When a user clicks on a video, it recognizes the product worn by the celebrity, and displays information on the screen on the most similar product corresponding to the recognized product, allowing them to go to the seller's site where they can purchase it. In order for such a system to operate stably, a pose estimation and siamese network-based system is proposed. The proposed system will primarily be released as a streaming service in the form of an app or web page that connects the products in web dramas or other K-pop video contents screened on the mobile with e-commerce. Furthermore, in the future, the technology is expected to be used globally in various industries such as smart mobility and display kiosks.

• International Journal of Advanced Culture Technology
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• v.12 no.1
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• pp.175-181
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• 2024

The paper examines the impact of digital media art on urban creative products, analyzing opportunities and challenges in the digital era. It emphasizes the development of urban cultural and creative products, highlighting their significance and future growth potential. The digital media era provides unprecedented innovation opportunities, utilizing advanced tools for efficient design, production, and marketing. Trends like personalization, customization, AI, and big data offer new expressions and market prospects. Cultural products evolve in design, marketing, and sales channels due to digital media, with tools like social media and e-commerce platforms opening new promotion avenues. Case studies illustrate digital media's role in driving innovation and enhancing user experiences. The paper addresses challenges in market competition, copyright, and technological renewal, while recognizing opportunities from AI and big data. The creative industries must adapt and innovate to remain relevant. Looking ahead, urban creative products will evolve under digitalization, relying on digital means to attract consumers and enhance brand value. Cultural products, beyond economic entities, disseminate urban culture and creative spirit. In the digital era, urban creative products demonstrate potential and necessity, prompting a reevaluation of digital technology's role. Through continuous innovation, this field contributes to cultural and economic levels, impacting urban characteristics and heritage. Urban creative products play an increasingly vital role in the global cultural and creative economy.

• Journal of the Korea Society of Computer and Information
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• v.25 no.9
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• pp.101-108
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• 2020

Recommender system is a must-have feature of e-commerce, since it provides customers with convenience in selecting products. Collaborative filtering is a widely-used and representative technique, where it gives recommendation lists of products preferred by other users or preferred by the current user in the past. Recently, researches on the recommendation system using deep learning artificial intelligence technologies are actively being conducted to achieve performance improvement. This study develops a collaborative filtering based recommender system using restricted Boltzmann machines of the deep learning technology by utilizing user ratings. Moreover, a learning parameter update algorithm is proposed for learning efficiency and performance. Performance evaluation of the proposed system is made through experimental analysis and comparison with conventional collaborative filtering methods. It is found that the proposed algorithm yields superior performance than the basic restricted Boltzmann machines.

• Journal of Information Management
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• v.36 no.4
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• pp.71-89
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• 2005

This paper examines the ways of using information resources available through information retrieval systems of portal sites. We analyze the types of information resources, search capabilities, and interfaces of Naver, Empas, and Google Scholar. Naver's retrieval system sells research reports, papers, patents information, etc. to users, which is similar to C2C(Customer to Customer in e-commerce environment). Empas provides information from journals, research reports, and proceedings with no charge. Google Scholar's noteworthy efforts are their collaborative programs with and/or for major U.S. libraries, such as "Library Link" and "Library Project." Considering the extended information retrieval services of portals, especially the services like Google Scholar's library programs, libraries need to develop more specialized services, such as the customized information service for individual user, development of user convenience tools like OCLC WorldCat, more accessibility through ubiquitous library concept, and collaboration among libraries.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.5B
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• pp.295-303
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• 2005

Recently, according to the rapid increase of Web users, various kinds of Web applications have been being developed. Hence, Web QoS(Quality of Service) becomes a critical issue in the Web services, such as e-commerce, Web hosting, etc. Nevertheless, most Web servers currently process various requests from Web users on a FIFO basis, which can not provide differentiated QoS. This paper presents a load balancing method to provide differentiated Web QoS in clustering web server. The first is the kernel-level approach, which is adding a real-time scheduling process to the operating system kernel to maintain the priority of user requests determined by the scheduling process of Web server. The second is the load-balancing approach, which uses IP-level masquerading and tunneling technology to improve reliability and response speed upon user requests. The third is the dynamic load-balancing approach, which uses the parameters related to the MIB-II of SNMP and the parameters related to load of the system such as memory and CPU.

• Journal of the Korea Convergence Society
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• v.8 no.4
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• pp.1-8
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• 2017

In the modern society, the size of the fashion market is continuously increasing both overseas and domestic. When purchasing a product through e-commerce, the evaluation data for the product created by other consumers has an effect on the consumer's decision to purchase the product. By analysing the consumer's evaluation data on the product the company can reflect consumer's opinion which can leads to positive affect of performance to company. In this paper, we propose a method to construct a model to analyze user's sentiment using word embedding space formed by learning review data of amazon fashion products. Experiments were conducted by learning three SVM classifiers according to the number of positive and negative review data using the formed word embedding space which is formed by learning 5.7 million Amazon review data.. Experimental results showed the highest accuracy of 88.0% when learning SVM classifier using 50,000 positive review data and 50,000 negative review data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.6B
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• pp.533-543
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• 2003

Recently, according to the rapid increase of Web users, various kinds of Web applications have been being developed. Hence, Web QoS(Quality of Service) becomes a critical issue in the Web services, such as e-commerce, Web hosting, etc. Nevertheless, most Web servers currently process various requests from Web users on a FIFO basis, which can not provide differentiated QoS. This paper presents two approaches to provide differentiated Web QoS. The first is the kernel-level approach, which is adding a real-time scheduling processor to the operating system kernel to maintain the priority of user requests determined by the scheduling processor of Web server. The second is the load-balancing approach, which uses If-level masquerading and tunneling technology to improve reliability and response speed upon user requests.

• The Journal of the Korea Contents Association
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• v.19 no.3
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• pp.171-182
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• 2019

As online shopping malls continue to grow in popularity, various chances of consumption are provided to customers. Customers decide the purchase by exploiting information provided by shopping malls such as the reviews of actual purchasing users, the detailed information of items, and so on. It is required to provide objective and reliable information because customers have to decide on their own whether the massive information is credible. In this paper, we propose a personalized recommendation method considering an item confidence to recommend reliable items. The proposed method determines user preferences based on various behaviors for personalized recommendation. We also propose an user preference measurement that considers time weights to apply the latest propensity to consume. Finally, we predict the preference score of items that have not been used or purchased before, and we recommend items that have highest scores in terms of both the predicted preference score and the item confidence score.

• Journal of the Korean Society of Clothing and Textiles
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• v.44 no.5
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• pp.1004-1018
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• 2020

Advances in e-commerce enable consumers to shop efficiently for fashion products in global markets in addition, the market size of purchasing directly from foreign websites are also increasing. This study investigates the effects of hedonic and utilitarian shopping values on the continuous use intention of online cross-border shopping. Curiosity and self-efficacy were introduced as mediating variables between shopping values and user intentions. A web-based survey is conducted on female consumers, who have experiences to buy fashion products by online cross-border shopping. A total of 472 responses were collected from a panel of online survey firms. Data are analyzed using confirmatory factor analysis, structural equation modeling, and multi-group SEM by AMOS 21.0. According to the results of the structural equation model test, hedonic value affected continuous use intention of online cross-border shopping as mediated by curiosity and self-efficacy; in addition, utilitarian value influenced self-efficacy, which mediated relations between the utilitarian value and the continuous use intention. The research model was also tested to compare heavy users and light users of online cross-border shopping. For heavy users, the effect of hedonic value on curiosity was significantly stronger than for light users. Several implications are suggested based on the results.

• Journal of the Korea Society of Computer and Information
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• v.26 no.8
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• pp.229-237
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• 2021

This paper aims to study the using motivation and influencing factors of Chinese users' participation in live stream shopping through theoretical and empirical analysis, so as to evaluate the change in users' needs and improve marketing strategies. In doing so, I conducted a questionnaire survey for Chinese live stream shopping users and collected the required data. For empirical analysis, I used SPSS and AMOS software to carry out descriptive analysis, reliability and validity analysis and structural equation model analysis (SEM) to test the hypothesis. The results of the analysis showed that core competency and brand personality of the short video industry have a significant impact on user and customer perceived value, thus influencing users' using motivation. That is, users do not blindly follow live stream shopping but make their active choice. Therefore, it is suggested that live stream shopping platform should strengthen the e-commerce attributes and eradicate "the sense of false satisfaction", in order to achieve the effective communication of information. On the other hand, to stimulate the purchase motivation of users, the brand should build up its personality, and enhance user and customer perceived value in cyber marketing.