• Proceedings of the Korea Contents Association Conference
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• 2018.05a
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• pp.495-496
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• 2018

사람의 피부는 개인마다 상태의 차이가 있으며, 개인의 피부 상태에 따가 피부고민도 다르다. 이에 따라, 일반 소비자들의 화장품 사용에 대한 선호도는 나만의 것, 내 피부에 맞는 화장품, 자세한 카운슬링 순으로 선호도가 나타나고 있다. 민간기관에서도 유전자 검사가 가능해짐으로써 상기와 같이 피부에 대한 유전자 분석도 활성화되고 있는 실정으로, 본 논문에서는 개인의 피부 유형과 유전자 정보를 고려하고 소셜 네트워크에서의 데이터를 수집하여 빅데이터 분석을 통한 맞춤형 추천 서비스를 제안한다.

• Ecology and Resilient Infrastructure
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• v.8 no.4
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• pp.273-280
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• 2021

In the past, the government made a total of 357 hydrophilic districts into parks to create rest areas in the national river with the four major river projects. According to the results of the survey, 60 water-friendly districts with low utilization were lifted in January 2017, and 297 water-friendly districts are currently being managed. Local governments are in charge of the maintenance costs necessary to maintain these hydrophilic districts, which require considerable costs, so it is necessary to accurately grasp the characteristics and needs of local residents at the operation stage after designation. In this study, the characteristics of local residents in the hydrophilic district were analyzed by correlating social factors with river users, crawling social network data to analyze visit patterns, and derived related Keywords, and analyzed the characteristics of the hydrophilic district. The study target areas are Samrak and Daejeo Ecological Park, located downstream of the Nakdonggang River. Social factors analyzed real estate transaction price data, economic activity income, households, stress perception rate, and pet breeding status through public data provided by Statistics Korea, and analyzed user visit patterns and image keywords on weekends.

• Journal of Intelligence and Information Systems
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• v.15 no.1
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• pp.87-102
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• 2009

With the growth of Web 2.0, lots of services allow yours to post their personal information and useful knowledges on networked information spaces such as blogs and online communities etc. As the services are generalized, recent researches related to social network have gained momentum. However, most social network services do not support machine-processable semantic knowledge, so that the information cannot be shared and reused between different domains. Moreover, as explicit definitions of relationships between individual social entities do not be described, it is difficult to analyze social network for inferring unknown semantic relationships. To overcome these limitations, in this paper, we propose a social network analysis system with personal photographic data up-loaded by virtual community users. By using ontology, an informative connectivity between a face entity extracted from photo data and a person entity which already have social relationships was defined clearly and semantic social links were inferred with domain rules. Then the inferred links were provided to yours as a visualized graph. Based on the graph, more efficient social network analysis was achieved in online community.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2089-2094
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• 2017

Altmetrics is the measurement index and quantitative data to complement the traditional indicators based on the citation. Altmetrics research has acquired greater importance in the past few years, partly due to the complement to the traditional bibliometrics. This paper aims to reveal the research status and trends in altmetrics research. A total of 187 articles from 2005 to 2017 are obtained and analyzed, illustrating a steady rise (S-mode) in altmetrics research since 2005. Using social network analysis and co-word analysis, the author cooperation network and keyword co-occurrence network are developed. The core scientists and eight international research groups are discovered, reflecting that researchers in this field have a low degree of cooperation. Four topics of altmetrics research are discovered by hierarchical clustering. The results can be useful for the advanced research of altmetrics.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.129-149
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• 2021

Recently, interest in social robots that can socially interact with humans is increasing. Thanks to the development of ICT technology, social robots have become easier to provide personalized services and emotional connection to individuals, and the role of social robots is drawing attention as a means to solve modern social problems and the resulting decline in the quality of individual lives. Along with the interest in social robots, the spread of social robots is also increasing significantly. Many companies are introducing robot products to the market to target various target markets, but so far there is no clear trend leading the market. Accordingly, there are more and more attempts to differentiate robots through the design of social robots. In particular, anthropomorphism has been studied importantly in social robot design, and many approaches have been attempted to anthropomorphize social robots to produce positive effects. However, there is a lack of research that systematically describes the mechanism by which anthropomorphism for social robots is formed. Most of the existing studies have focused on verifying the positive effects of the anthropomorphism of social robots on consumers. In addition, the formation of anthropomorphism of social robots may vary depending on the individual's motivation or temperament, but there are not many studies examining this. A vague understanding of anthropomorphism makes it difficult to derive design optimal points for shaping the anthropomorphism of social robots. The purpose of this study is to verify the mechanism by which the anthropomorphism of social robots is formed. This study confirmed the effect of the human-likeness of social robots(Within-subjects) and the construal level of consumers(Between-subjects) on the formation of anthropomorphism through an experimental study of 3×2 mixed design. Research hypotheses on the mechanism by which anthropomorphism is formed were presented, and the hypotheses were verified by analyzing data from a sample of 206 people. The first hypothesis in this study is that the higher the human-likeness of the robot, the higher the level of anthropomorphism for the robot. Hypothesis 1 was supported by a one-way repeated measures ANOVA and a post hoc test. The second hypothesis in this study is that depending on the construal level of consumers, the effect of human-likeness on the level of anthropomorphism will be different. First, this study predicts that the difference in the level of anthropomorphism as human-likeness increases will be greater under high construal condition than under low construal condition.Second, If the robot has no human-likeness, there will be no difference in the level of anthropomorphism according to the construal level. Thirdly,If the robot has low human-likeness, the low construal level condition will make the robot more anthropomorphic than the high construal level condition. Finally, If the robot has high human-likeness, the high construal levelcondition will make the robot more anthropomorphic than the low construal level condition. We performed two-way repeated measures ANOVA to test these hypotheses, and confirmed that the interaction effect of human-likeness and construal level was significant. Further analysis to specifically confirm interaction effect has also provided results in support of our hypotheses. The analysis shows that the human-likeness of the robot increases the level of anthropomorphism of social robots, and the effect of human-likeness on anthropomorphism varies depending on the construal level of consumers. This study has implications in that it explains the mechanism by which anthropomorphism is formed by considering the human-likeness, which is the design attribute of social robots, and the construal level of consumers, which is the way of thinking of individuals. We expect to use the findings of this study as the basis for design optimization for the formation of anthropomorphism in social robots.

• The Journal of Bigdata
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• v.2 no.1
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• pp.71-75
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• 2017

The topic of big data has gained attention from the industry and the academics, because of the revitalization of social network services. The purpose of this study is to analyze the application cases of big data according to the categories of U-City services. The result from this study is that inside and unstructured information is more applied than outside and structured information in order to generate big data.

• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.19-30
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• 2012

Based on the internet-based infrastructures such as various information devices, social network systems and cloud computing environments, distributed and sharable data are growing explosively. Recently, as a data analysis and mining technique for extracting, analyzing and classifying the inherent and useful knowledge and information, Formal Concept Analysis on binary or many-valued data has been successfully applied in many diverse fields. However, in formal concept analysis, there has been little research conducted on analyzing interval data whose attributes have some interval values. In this paper, we propose a new approach for classification of interval data based on the formal concept analysis. We present the development of a supporting tool(iFCA) that provides the proposed approach for the binarization of interval data table, concept extraction and construction of concept hierarchies. Finally, with some experiments over real-world data sets, we demonstrate that our approach provides some useful and effective ways for analyzing and mining interval data.

• Journal of Communication Design
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• v.63
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• pp.336-347
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• 2018

Nowadays, in Korea, the number of campers is increased over 5 million. Many Korean camping brands have excellent qualities however, a lot of times weak brand identities to be globally known. The purpose of this study is to provide helpful sources to have strong brand identities, add more values based on related word research from big data and market research. The data is to be analysed by sensible & cognitive approaches. The keywords for the sensible research are 'camping, camp, camping brand, and camping design'. Then 17 representative oversea brands and 10 Korean brands were analysed for the market researches. From related word research from big data, we can find out the thinking process of potential consumers, how people communicates to exchange information, and what can be the sources to add brand values. Also from the market researches, we were able to find that successful brands have distinctive brand identities, stories, logos with representable colors and they continuous produce signature designs and own way of color matching.

• Journal of Digital Convergence
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• v.13 no.8
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• pp.161-168
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• 2015

Given social problems of social network service (SNS) addiction, it is critical to understand user's formation mechanism of SNS addiction. Since a number of studies have demonstrated the negative outcomes of excessive SNS use, the researchers examined important antecedents of SNS addiction as SNS habit that is considered as a key driver of SNS addiction. Moreover, the effects of self-expression, network management, and information search on SNS addition formation were investigated. The proposed theoretical model was empirically tested by using longitudinal survey data collected from 206 Facebook users. The analysis results indicate that SNS habit plays an important role in forming SNS addiction. Further, self-expression, network management, and information search influence SNS addiction through SNS habit. The analysis results offer some in-depth perspectives to SNS providers and government that establish policies or digital convergence strategies to induce healthy SNS use.

• Journal of Korean Society of Forest Science
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• v.108 no.1
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• pp.116-126
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• 2019

The production volume and amount of non-timber forest products in Korea has been on the increase for the past five years. In particular, the production amount of wild vegetables (edible mountain plants) is approximately KRW 400 billion as of 2017, accounting for 14 % of the total production amount of non-timber forest products. Among wild vegetables, especially the production volumes and amounts of bracken, saw-wort (Saussurea), and thistle have grown steadily. Nevertheless, severe price competition with cheap imports and little changes in the pattern of wild vegetable consumption may negatively affect the prices of domestic wild vegetables. This, in turn, can decrease the overall consumption of wild vegetables. Recently, however, consumers have preferred healthy food with increases in their income and interest in health. Therefore, now is a crucial time for the wild vegetable market. Accordingly, this study analyzed consumers' purchase and consumption behavior related to wild vegetables through a consumer survey to contribute to establishing various strategies and policies for promoting the consumption of these vegetables. Also, this study identified consumers' awareness and intention regarding wild vegetables by analyzing social big data. Different from previous studies, this study investigated consumers' awareness and intention by analyzing SNS social big data, as well as conducting a survey. The results of the study will help prioritize strategies and policies for boosting the consumption of wild vegetables.