• The Journal of the Korea Contents Association
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• v.20 no.8
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• pp.42-53
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• 2020

With the development of social network services, graph structures have been utilized to represent relationships among objects in various applications. Recently, a demand of subgraph matching in real-time graph streams has been increased. Therefore, an efficient approximate Top-k subgraph matching scheme for low latency in real-time graph streams is required. In this paper, we propose an approximate Top-k subgraph matching scheme considering data reuse in graph stream environments. The proposed scheme utilizes the distributed stream processing platform, called Storm to handle a large amount of stream data. We also utilize an existing data reuse scheme to decrease stream processing costs. We propose a distance based summary indexing technique to generate Top-k subgraph matching results. The proposed summary indexing technique costs very low since it only stores distances among vertices that are selected in advance. Finally, we provide k subgraph matching results to users by performing an approximate Top-k matching on the summary indexing. In order to show the superiority of the proposed scheme, we conduct various performance evaluations in diverse real world datasets.

• The Journal of the Korea Contents Association
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• v.14 no.6
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• pp.54-62
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• 2014

Crowdfunding, a way of raising small size investments or donations from numerous individuals, mostly through internet to fund a project, has attracted global interests. The growth of the social network platform has made crowdfunding easier especially for those in the arts and culture sector. Despite the growth of such vehicle, there has been not much empirical research on the subject. We investigated the relationships between the information in the web sites and its contribution to the success in fundraising. We have sampled 161 projects that were uploaded on Tumblbug.com and studied the type of information that lead to a successful fund raise. As a result, we fould that the contents characteristics including motion-pictures, images, and lengthy texts have positive impacts on the success of fundraising. Fundraising rewards did not show any impacts.

• Journal of the Korea Safety Management & Science
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• v.19 no.2
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• pp.173-180
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• 2017

Omni-channel strategy is an innovative paradigm for integrated information distribution of inventory, sales, operations, marketing, delivery, pickups and returns in supply chain management. Recently the distribution strategy faces new challenges with the advent of mobile distribution channels. Social media with countless apps imposes additional stress on supply chain operations. Due to these changes, distribution network in supply chain is changing naturally and rapidly from multi-channel to omnni-channel platform. Recently numerous domestic distributors establish and adapt this new supply chain optimization tool as a part of seamless flow of movements of goods from one channel to other channels. The objective of this paper is to present a preliminary findings on how omnni-channel affects the supply chain management. A survey is used to ascertain in the degree of omnni-channel implementation and statistical evidence is provided to test sets of hypothesis. The results of the questionnaire showed that consumers' purchasing styles differed by gender, age, purchase purpose, and product type. In particular, women consider purchasing experience in omni-channel to be important. As food and household goods can be conveniently shipped, consumers prefer online purchasing it. Conversely, consumers tend to favor omni-channel strategy in connection with offline experience in IT products.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.10B
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• pp.957-964
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• 2003

The circulation of unwholesome information such as obscene and violent information is gradually increasing based on the rapid expansion of information communications infrastructure. Those kinds of information are harmful to the adolescents and even cause social problems so that active countermeasure is requited. In order to cope with the spread of unwholesome information, appropriate regulating methods are absolutely in need by establishing or revising information communications-related laws. In this paper, we had analyzed domestic and foreign programs with existing harmful information blocking method, and then designed and implemented a selective blocking program based on Platform for Internet Contents Selection(PICS) by using selective blocking technology based on Internet contents rating system. We also proposed a compromised rating system blocking method that consists of selective filtering function by age and the popular blocking list. The proposed system has advantages in that there would be no increase in network load resulting from blocking list update and inquiry, it is possible to perform active selective filtering considering user's age, and it may introduce self-imposed rating.

• KIPS Transactions on Computer and Communication Systems
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• v.5 no.2
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• pp.33-40
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• 2016

Due to the growth of social network systems (SNS), big data are realized and Hadoop was developed as a distributed platform for analyzing big data. Enterprises analyze data containing users' sensitive information by using Hadoop and utilize them for marketing. Therefore, researches on data encryption have been done to protect the leakage of sensitive data stored in Hadoop. However, the existing researches support only the AES encryption algorithm, the international standard of data encryption. Meanwhile, Korean government choose ARIA algorithm as a standard data encryption one. In this paper, we propose a HDFS data encryption scheme using ARIA algorithms on Hadoop. First, the proposed scheme provide a HDFS block splitting component which performs ARIA encryption and decryption under the distributed computing environment of Hadoop. Second, the proposed scheme also provide a variable-length data processing component which performs encryption and decryption by adding dummy data, in case when the last block of data does not contains 128 bit data. Finally, we show from performance analysis that our proposed scheme can be effectively used for both text string processing applications and science data analysis applications.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.2
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• pp.139-148
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• 2019

The paper proposes an analytical framework for the impact of technical change on business model innovation. Based upon the examination of the relationship between the mission of business and technology, it introduces classification of technology-based business models such as problem-solving model, production model and network model, respectively employing intensive technology, interlinked technology and mediating technology as a key technology. The discussion of various cases of business model innovation shows that the impact of digital technology is first translated into the value generation in terms of efficiency or effectiveness. These new values then enable a new business model which is based on a different key technology through business model shift, expansion, unbundling, or platform. Quite often those business model changes involves system-wide innovation. The framework for the analysis of the impact of technical change on business model innovation is presented with directions for future research.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.32 no.1
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• pp.133-150
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• 2021

The purpose of this study is to identify the applicability of machine learning targeting titles in the classification of books in public libraries. Data analysis was performed using Python's scikit-learn library through the Jupiter notebook of the Anaconda platform. KoNLPy analyzer and Okt class were used for Hangul morpheme analysis. The units of analysis were 2,000 title fields and KDC classification class numbers (300 and 600) extracted from the KORMARC records of public libraries. As a result of analyzing the data using six machine learning models, it showed a possibility of applying machine learning to book classification. Among the models used, the neural network model has the highest accuracy of title classification. The study suggested the need for improving the accuracy of title classification, the need for research on book titles, tokenization of titles, and stop words.

• The Journal of the Korea Contents Association
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• v.20 no.12
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• pp.36-48
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• 2020

App market has continuously been growth since its launch. The market revenues will reach about 1,000 billion US dollars in 2019. App is a core service for smartphone. Currently, there are more than 1.5 million mobile apps in App platform calling out for attention. So, if you are looking at developing a successful app, you need to have a solid marketing and distribution strategy. Online word of mouth(eWOM) is one of the most effective, powerful App marketing method. eWOM affect potential consumers' decision making, and this effect can spread rapidly through online social network. Despite the increasing research on word of mouth, only few studies have focused on content analysis. Most of studies focused on the causes and acceptance of eWOM and eWOM performance measurement. This study aims to content analysis of mobile apps review In 2013, Google researchers announced Word2Vec. This method has overcome the weakness of previous studies. This is faster and more accurate than traditional methods. This study found out the relationship between mobile app reviews and checked for reactions by Word2vec.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.475-480
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• 2021

With the rapid development of mobile, cloud computing technology and social network services, we are in the flood of huge data and realize that these large-scale data contain very precious value and important information. Big data, however, have both latent useful value and critical risks, so, nowadays, a lot of researches and applications for big data has been executed actively in order to extract useful information from big data efficiently and make the most of the potential information effectively. At this moment, the data analysis technique that can extract precious information from big data efficiently is the most important step in big data computing process. In this study, we investigate various data analysis techniques that can extract the most useful information in big data computing process efficiently, compare pros and cons of those techniques, and propose proper data analysis method that can help us to find out the best solution of the big data analysis in the peculiar situation.

• Journal of dental hygiene science
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• v.22 no.4
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• pp.241-248
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• 2022

Background: Plastic waste generates pollutants in the process of incineration or landfilling, and accumulates in water or marine organisms, causing adverse effects on the environment and the human body. Recently, various eco-friendly oral hygiene products (Eco-OHPs) such as bamboo toothbrushes and biodegradable plastic toothbrushes have been developed. Therefore, this study aimed to investigate the current level of awareness and purchasing status of eco-OHPs among adults who are interested in eco-friendly products. Methods: This study included adults aged >19 years who regularly visited eco-friendly shops and online sites; the online survey links were distributed during their visits to eco-friendly Internet cafés and companies. Of the 22 questions, seven assessed the participants' general characteristics, three assessed the general oral hygiene care products used, six assessed the level of awareness of Eco-OHPs, and six assessed the purchasing status of Eco-OHPs. Frequency analysis, chi-square test, and regression analysis were performed using SPSS software. Results: Among the respondents, 108 (51.4%) were aware of Eco-OHPs, and 79 (37.6%) had experience purchasing Eco-OHPs. The most common reason for not purchasing was the lack of information about related brands or products (74, 56.5%). The most common platform used in obtaining information was the Internet (general: 31.5%, eco-friendly: 46.3%), such as Social Network Service, Internet cafes, and blogs. The experience in purchasing Eco-OHPs was affected by whether the respondents recognized the possibility of contributing to environmental preservation, availability of vendors, product safety, and the number of eco-friendly products purchased. Conclusion: In order to expand the use of Eco-OHPs, various efforts such as promotion of eco-friendly characteristics, determination of related vendors, reliable analysis of product safety, and expansion of product experience opportunities are required.