• 한국멀티미디어학회논문지
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• 제17권9호
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• pp.1125-1133
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• 2014

Recently, there are many researches have been studying for analyzing user interests and emotions based on users profiles and diverse information from Social Network Services (SNSs) due to their popularities. However, most of traditional researches are focusing on their researches based on single resource such as text, image, hash tag, and more, in order to obtain what user emotions are. Hence, this paper propose a method for obtaining user emotional information by analyzing texts and images both from Instagram which is one of the well-known image based SNSs. In order to extract emotional information from given images, we firstly apply GRAB-CUT algorithm to retrieve objects from given images. These retrieved objects will be regenerated by their representative colors, and compared with emotional vocabulary table for extracting which vocabularies are the most appropriate for the given images. Afterward, we will extract emotional vocabularies from text information in the comments for the given images, based on frequencies of adjective words. Finally, we will measure WUP similarities between adjective words and emotional words which extracted from the previous step. We believe that it is possible to obtain more precise user emotional information if we analyzed images and texts both time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권6호
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• pp.2450-2469
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• 2018

In this paper, we develop a spatiotemporal model to analysis of cellular user in underlay D2D communication by using stochastic geometry and queuing theory. Firstly, by exploring stochastic geometry to model the user locations, we derive the probability that the SINR of cellular user in a predefined interval, which constrains the corresponding transmission rate of cellular user. Secondly, in contrast to the previous studies with full traffic models, we employ queueing theory to evaluate the performance parameters of dynamic traffic model and formulate the cellular user transmission mechanism as a M/G/1 queuing model. In the derivation, Embedded Markov chain is introduced to depict the stationary distribution of cellular user queue status. Thirdly, the expressions of performance metrics in terms of mean queue length, mean throughput, mean delay and mean dropping probability are obtained, respectively. Simulation results show the validity and rationality of the theoretical analysis under different channel conditions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권3호
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• pp.1742-1760
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• 2017

Recent evolution in the open access internet technology demands that the identifying information of a user must be protected. Authentication is a prerequisite to ensure the protection of user identification. To improve Qu et al.'s scheme for remote user authentication, a recent proposal has been published by Huang et al., which presents a key agreement protocol in combination with ECC. It has been claimed that Huang et al. proposal is more robust and provides improved security. However, in the light of our experiment, it has been observed that Huang et al.'s proposal is breakable in case of user impersonation. Moreover, this paper presents an improved scheme to overcome the limitations of Huang et al.'s scheme. Security of the proposed scheme is evaluated using the well-known random oracle model. In comparison with Huang et al.'s protocol, the proposed scheme is lightweight with improved security.

• 한국융합학회논문지
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• 제11권7호
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• pp.1-7
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• 2020

모바일 디바이스의 성능이 급격히 향상됨에 따라 사용자는 많은 작업을 모바일 환경에서 할 수 있게 되었다. 이는 모바일 디바이스에 저장된 행태 정보를 활용하면 사용자의 많은 부분을 알 수 있음을 의미한다. 예를 들어, 사용자의 문자 메시지와 자주 사용하는 어플리케이션 정보(행태 정보)를 활용하여 사용자가 육아에 관심이 있는지와 같은 유용한 정보(프로파일 예측)를 만들 수 있다. 본 연구에서는 모바일 디바이스에서 수집할 수 있는 사용자의 행태 정보를 알아보고, 이를 활용하여 사용자를 프로파일링 할 수 있는 항목을 제안한다. 그리고 프로파일링 결과를 활용하여 사용자에게 편의를 줄 수 있는 정보로 활용할 수 있는 방안도 함께 제시한다.

• Journal of Information Science Theory and Practice
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• 제6권3호
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• pp.25-36
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• 2018

Anonymity plays an increasingly important role on social media. This is reflected by more and more applications enabling anonymous interactions. However, do social media users behave different when they are anonymous? In our research, we investigated social media services meant for solely anonymous use (Jodel) and for widely spread non-anonymous sharing of pictures and videos (Instagram). This study examines the impact of anonymity on the behavior of users on Jodel compared to their non-anonymous use of Instagram as well as the differences between the user types: producer, consumer, and participant. Our approach is based on the uses and gratifications theory (U>) by E. Katz, specifically on the sought gratifications (motivations) of self-presentation, information, socialization, and entertainment. Since Jodel is mostly used in Germany, we developed an online survey in German. The questions addressed the three different user types and were subdivided according to the four motivation categories of the U>. In total 664 test persons completed the questionnaire. The results show that anonymity indeed influences users' usage behavior depending on user types and different U> categories.

• 한국정보시스템학회지:정보시스템연구
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• 제17권1호
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• pp.23-43
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• 2008

Nowadays, openness and accessibility of information systems increase security threats from inside and outside of organization. Appropriate password is supposed to bring out security effects such as preventing misuses and banning illegal users. This study emphasizes on choosing passwords from perspective of information security and investigated user's security awareness affecting behavioral intention. The research model proposed in this study includes user's security belief which is influenced by risk awareness factors such as information assets, threats and vulnerability elements. The risk awareness factors ale derived from risk analysis methodologies for information security. User's risk awareness is a factor influencing the security belief, attitude toward security behavior, and security behavioral intention. According to the result of this study, while vulnerability is not related to the risk awareness, information assets and threats are related to the user's risk awareness. There is a significant relationship between risk awareness and security belief. Also, user's security behavioral intention is significantly affected by security attitude.

• 한국정보시스템학회지:정보시스템연구
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• 제15권1호
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• pp.145-168
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• 2006

Current computer viruses are one of the most serious problems in information age due to their potential demage and impact on use of information systems. To make the problem worse, virus development technology has been advanced rapidly, and use of network systems has expanded widely. Therefore computer viruses are much more complex and use of anti-virus software(AV S/W) is not enough to prrevent virus incidents. It implies that computer viruses as well as other information security matters are not solely a technical problem but also a managerial one. This study emphasized on computer virus controls from managerial perspective of information security and investigated factors influencing the effectiveness of computer virus controls. Organization's comprehensive security policies provide guidelines on how organization or individual can protect themselves from computer viruses. Especially, user's education has positive impact on user's security related characteristics. Based on the analysis of research model using structural equation modeling technique, security policies were influencing security controls and improving user's computer viruses related awareness. Also security controls had positive impact on security effectiveness. However, no significant relationship was found between user's security related characteristics and security effectiveness.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2016년도 추계학술대회
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• pp.784-786
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• 2016

최근 건강과 관련된 다양한 시스템들에 대한 연구가 진행되고 있다. 이에 반해 사용자의 신체 정보를 정확하게 분석하고 이에 따른 정보를 제공해주는 시스템들은 개발 단계이거나 정확도가 미흡한 수준이다. 이를 해결하기 위해 본 논문에서는 사용자의 신체 정보를 분석하는 알고리즘을 제시하고 이를 기반으로 한 피트니스 시스템을 제안한다. 사용자의 신체 정보를 분석하는 알고리즘은 사용자의 신장과 체중을 분석하여 BMI(Body Mass Index) 지수와 BMR(Basal Metabolic Rate) 수치를 계산한다. 제안하는 시스템은 계산된 BMI 지수와 BMR 수치를 바탕으로 사용자에게 적합한 운동량을 추천해줄 수 있을 것으로 사료된다.

• Journal of Information Processing Systems
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• 제19권3호
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• pp.310-322
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• 2023

Although the network environment is gradually improving, the virtual nature of the network is still the same fact, which has brought a great influence on the supervision of Weibo network public opinion dissemination. In order to reduce this influence, the user information of Weibo network public opinion dissemination is studied by using Python technology. Specifically, the 2019 "Ethiopian air crash" event was taken as the research subject, the relevant data were collected by using Python technology, and the data from March 10, 2019 to June 20, 2019 were constructed by using the implicit Dirichlet distribution topic model and the naive Bayes classifier. The Weibo network public opinion user identity graph model under the "Ethiopian air crash" on June 20 found that the public opinion users of ordinary netizens accounted for the highest proportion and were easily influenced by media public opinion users. This influence is not limited to ordinary netizens. Public opinion users have an influence on other types of public opinion users. That is to say, in the network public opinion space of the "Ethiopian air crash," media public opinion users play an important role in the dissemination of network public opinion information. This research can lay a foundation for the classification and identification of user identity information types under different public opinion life cycles. Future research can start from the supervision of public opinion and the type of user identity to improve the scientific management and control of user information dissemination through Weibo network public opinion.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1986-1989
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• 2003

This paper proposes the information retrieval improvement for the Web using the structure and hyperlinks of HTML documents along with user profile. The method bases on the rationale that terms appearing in different structure of documents may have different significance in identifying the documents. The method partitions the occurrence of terms in a document collection into six classes according to the tags in which particular terms occurred (such as Title, H1-H6 and Anchor). We use genetic algorithm to determine class importance values and expand user query. We also use this value in similarity computation and update user profile. Then a genetic algorithm is used again to select some terms from user profile to expand the original query. Lastly, the search engine uses the expanded query for searching and the results of the search engine are scored by similarity values between each result and the user profile. Vector space model is used and the weighting schemes of traditional information retrieval were extended to include class importance values. The tested results show that precision is up to 81.5%.