• Proceedings of the Korean Information Science Society Conference
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• 2012.06c
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• pp.295-297
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• 2012

내부자에 의한 위협이 증가됨에 따라, 기업 내 핵심기술이 유출되어 큰 피해가 발생하고 있다. 내부자들이 합법적인 권한을 통한 불법적인 정보유출을 시도하는 위험을 예측 관리하기 위하여, 본 논문에서는 내부자들의 위험도를 평가하기 적합한 위험분석 방법론 ISMS-AIR(ISMS - Against Insider Risk)을 제안하였다. 내부자 위협의 정의와 위험도 평가를 위한 기존 위험분석 방법론들을 연구하였으며, 기존 자산 중심의 위험분석 방법론인 ISMS에 사용자 중심의 행위 모니터링을 강화하여 위험도 산출하는 방법을 제안하였다. 이를 위하여 사용자 행위에 따른 프로파일링 데이터와 이상징후 시나리오를 적용하여 내부자들의 위험도를 산출하고, 주요 모니터링 대상을 선정하여 내부자들의 불법적인 정보유출 시도행위를 모니터링 할 수 있다.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10c
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• pp.233-238
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• 2007

학술연구정보 서비스는 연구자의 연구 개발 과정에서 필수적으로 활용해야 하는 서비스이다. 그렇지만, 그 중요성에 비해 아직까지 학술연구정보 서비스에 대한 심도 깊은 사용성 평가가 제대로 이루어지고 있지 않다. 본 연구는 OntoFrame이라는 시맨틱 웹 기술 기반 학술연구정보 서비스 구현 과정에서 반복적인 사용성 평가를 수행함으로써 어떻게 서비스가 효용성과 사용성을 갖추어가는 지를 실증함으로써 사용성 평가의 중요성을 강조하고자 한다. 특히, 사용성 평가 목표에 따라 서비스 시안(Mock-up)을 대상으로 실시한 사용자 인터뷰 중심의 1차 사용성 평가와 서비스 프로토타입을 대상으로 실시한 학술연구 정보 서비스간 비교 평가 중심의 2차 사용성 평가를 상이하게 구성함으로써 사용성 관련 문제를 다양한 관점에서 도출할 수 있었다. 사용성 평가는 매 구현 단계마다 반복적으로 실시함으로써 본 학술연구정보 서비스의 사용성을 지속적으로 향상시킬 계획이다.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.715-725
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• 2022

With the development of digital technology related to mobile, cloud, IoT, even traditional businesses have began to develop strategies for digital transformation. This is regarded as a very important part for business sustainability. However, many of these attempts are being conducted from the management point of view, and there has been little research on user experience design for digital transformation. In this study, Starbucks, which started a offline store business and expanded its experience with online services, was selected as a representative case and user research was conducted on it. Through an usability evaluation and post-task interviews of the Starbucks mobile application users, we discovered important issues of user experience to consider when transforming and expanding services online from offline. Based on the findings, the considersations for designing online user experience were discussed and proposed. These are expected to contribute to the process of researching and implementing digital transformation.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10b
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• pp.189-193
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• 2006

문맥광고 또는 컨텍스트 기반 광고란 사용자들이 선택한 웹 콘텐츠 내용을 기반으로 하여 연관성 있는 광고를 자동으로 선택하여 사용자에게 제공하는 광고기법이다. 즉, 웹 사이트를 방문하는 고객을 타겟으로 하여 그들이 찾고자 하는 것과 관련된 광고를 내보냄으로써 효과적인 광고가 이루어지도록 하는 것이다. 그러나 기존의 문맥광고는 사용자가 관심을 가지는 키워드가 아닌 광고주가 선택한 키워드를 중심으로 광고 내용을 선택하기 때문에 사용자의 실제적인 관심이 반영되지 않아 광고의 효과가 떨어지는 문제점을 가지고 있다. 이러한 문제를 해결하기 위해 본 논문에서는 사용자가 웹 콘텐츠를 선택할 때 마다 사용자의 선호도를 동적으로 학습하고, 학습된 선호도를 문맥광고에 활용하는 개인화된 문맥광고를 제안한다. 실험을 위해서 제안한 방법으로 광고를 생성해서 보여주는 웹 브라우저를 구현하여 기존의 문맥광고와 개인화된 문맥광고에 대한 사용자의 평가를 비교하였다. 실험 결과 본 논문에서 제안한 개인화된 문맥광고가 ‘콘텐츠의 내용과의 연관성’, ‘사용자의 클릭여부’ 등의 항목에서 기존의 문맥광고에 비해 우수하다는 결과를 얻을 수 있었다.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.113-127
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• 2016

Among the techniques for recommendation, collaborative filtering (CF) is commonly recognized to be the most effective for implementing recommender systems. Until now, CF has been popularly studied and adopted in both academic and real-world applications. The basic idea of CF is to create recommendation results by finding correlations between users of a recommendation system. CF system compares users based on how similar they are, and recommend products to users by using other like-minded people's results of evaluation for each product. Thus, it is very important to compute evaluation similarities among users in CF because the recommendation quality depends on it. Typical CF uses user's explicit numeric ratings of items (i.e. quantitative information) when computing the similarities among users in CF. In other words, user's numeric ratings have been a sole source of user preference information in traditional CF. However, user ratings are unable to fully reflect user's actual preferences from time to time. According to several studies, users may more actively accommodate recommendation of reliable others when purchasing goods. Thus, trust relationship can be regarded as the informative source for identifying user's preference with accuracy. Under this background, we propose a new hybrid recommender system that fuses CF and social network analysis (SNA). The proposed system adopts the recommendation algorithm that additionally reflect the result analyzed by SNA. In detail, our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and trust relationship information between users when calculating user similarities. For this, our system creates and uses not only user-item rating matrix, but also user-to-user trust network. As the methods for calculating user similarity between users, we proposed two alternatives - one is algorithm calculating the degree of similarity between users by utilizing in-degree and out-degree centrality, which are the indices representing the central location in the social network. We named these approaches as 'Trust CF - All' and 'Trust CF - Conditional'. The other alternative is the algorithm reflecting a neighbor's score higher when a target user trusts the neighbor directly or indirectly. The direct or indirect trust relationship can be identified by searching trust network of users. In this study, we call this approach 'Trust CF - Search'. To validate the applicability of the proposed system, we used experimental data provided by LibRec that crawled from the entire FilmTrust website. It consists of ratings of movies and trust relationship network indicating who to trust between users. The experimental system was implemented using Microsoft Visual Basic for Applications (VBA) and UCINET 6. To examine the effectiveness of the proposed system, we compared the performance of our proposed method with one of conventional CF system. The performances of recommender system were evaluated by using average MAE (mean absolute error). The analysis results confirmed that in case of applying without conditions the in-degree centrality index of trusted network of users(i.e. Trust CF - All), the accuracy (MAE = 0.565134) was lower than conventional CF (MAE = 0.564966). And, in case of applying the in-degree centrality index only to the users with the out-degree centrality above a certain threshold value(i.e. Trust CF - Conditional), the proposed system improved the accuracy a little (MAE = 0.564909) compared to traditional CF. However, the algorithm searching based on the trusted network of users (i.e. Trust CF - Search) was found to show the best performance (MAE = 0.564846). And the result from paired samples t-test presented that Trust CF - Search outperformed conventional CF with 10% statistical significance level. Our study sheds a light on the application of user's trust relationship network information for facilitating electronic commerce by recommending proper items to users.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.04a
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• pp.34-34
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• 1993

• Journal of Digital Convergence
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• v.15 no.4
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• pp.443-449
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• 2017

Since usage of smartphone becomes popular, Ecology of smart media based on smartphone is creating new ecological system of information. This research is for evaluating usability and sustainability of application due to development of smartphone usage in these days. For the research, precedent researches were analyzed and hypothesis were set up based on those researches. Then, iCloud Calendar and Never Calendar, which are two major calendar applications, were evaluated by in-depth interview and measuring task performance time of interviewees, and used these results to verify hypothesis. Then verify hypothesis through the research and analyze which type of users focus on aesthetic impression, and which users focus on usability and practicality. This research is to analyze success and failure points of Calendar Applications' user experience design, and suggests guideline for future transformation of offline to online.

• Journal of Communication Design
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• v.57
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• pp.256-271
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• 2016

We attempted to implement Human Centered Design(HCD) according to the following three steps : (1) deriving user needs, (2) conducting ideation based the derived user needs, and (3) developing design concepts. The research on users and experts requires substantial time and cost, and there has not been an effective and clear-cut means to validate the research results before developing design concepts. We therefore extended the means of usability test to a context-based character. We applied this test for the development of design for Wearable Cardioverter-Defibrillator(WCD). Would this test be applied to various cases in the fields of medical equipment/apparatus development - which relatively takes a longer time to be developed - it would aid in accumulating and categorizing the reference data for variables incorporated for evaluating such cases. Future studies are needed to complement our findings concerning context-based usability tests.

• Journal of Digital Convergence
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• v.18 no.11
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• pp.233-239
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• 2020

Due to the development of digital technology, users can record their daily lives without being restricted by time and space. The trend is growing rapidly, but lifelogging cases are still insufficient. Google's Timeline and domestic application 'Daily' were analyzed through in-depth interviews. Based on the Creating Pleasurable Interface Model, the factors influencing user satisfaction were identified by the Reckard 7-point scale based on the Honeycomb model. The results of the in-depth interviews and the 7-point scale were similar, and we could see what and why users preferred the recording application. This study is meaningful to evaluate the user experience for recording application and analyzing the needs of users obtained through in-depth interviews to assess the usability that provide a service record and recall.

• Journal of the Korea Convergence Society
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• v.8 no.9
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• pp.271-276
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• 2017

This project has been conducted to improve the usability of Chatbot Services such as Google(Allo) and Facebook M(Messenger. Based on the evaluation, this study aims to suggest the solutions to improve the usability of domestic Chatbot services and future directions for their development. It provides the overall understanding of the AI Chatbot service and the feature of Chatbot service through literature search. Furthermore, we summarized the current standing and the prospect of domestic messenger-based assistant Chatbot services. For conducting user evaluation, Peter Morville's honeycomb model is applied to in-depth user interviews. The followings are elements that could be amended to improve the service. The service should be incorporated by intuitive elements for users' understanding its functions and eliminate any elements that interfere with usability. The accuracy should be increased to improve the user satisfaction. This research will provide the future guidelines to improve the usability of Chabot services through continuous evaluation by users.