• Proceedings of the KIEE Conference
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• 2008.11a
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• pp.348-350
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• 2008

본 논문의 목표는 한국 전력에서 의뢰한 용량 과제를 리뷰하기 위한 것이다. 한국 전력은 현재 책정된 용량 가격(CP)을 최적화하려고 한다. 이러한 과정에서 한국 전력과 발전사들 간에 논란이 있었다. 우리 연구팀은 중립적인 입장에서 한국 계통의 안정성에 초점을 맞추어 연구를 진행하였다. 본 리뷰에서 다룬 내용은 한국 계통의 적정 설비 예비율을 구하기 위해, Loss of Load Probability-이하 LOLP를 산출하는 과정을 시뮬레이션을 통해 보여주는 것이다. 더 정확한 결과를 산출하기 위해 2007년 실제부하 및 설비 용량 자료가 사용되었다. 또한 본 연구에서 진행된 여러 가지 과제 수행 단계 중, 본 논문은 2번째 단계인 적정 설비 예비율을 12${\sim}$15%로 하향시킬 가능성을 찾는 연구를 설명한다. 한국 전력 계통의 안정성 모델을 만들고, 그 모델을 사용하여 기존 LOLP에 맞는 적정 설비 예비율을 찾는다.

• Journal of Korea Game Society
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• v.22 no.1
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• pp.87-98
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• 2022

With the development of fourth industrial revolution-related technology and increased demands for non-face-to-face services, VR games attract attention. This study collected VR game review data from an online game platform STEAM and analyzed chronical trends using text mining and word cloud analysis. According to the results, experience and perceived cost were major trends from 2016 to 2017, increased demands for FPS and rhythm games were from 2018 to 2019, and story and immersion were from 2020 to 2021. It aims to contribute to expanding the base of VR games by identifying the keywords VR users take interest in by period.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.6
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• pp.1-8
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• 2019

Recently, consumer distrust has deepened due to blog posts focusing only on public relations due to 'viral marketing'. In addition, marketing projects such as false writing or exaggerated use of the latter phase are one of the most popular programs in 2016 as they are cheaper and more effective than newspaper and TV ads, and the size of advertising costs is set to be a major means of advertising at '3 trillion 394.1 billion won. From this 'viral marketing,' it has become an Internet environment that needs tools to filter information. The fake review filtering application ADDAVICHI presented in this paper extracts, analyzes, and presents blog keywords, total number of searches, reliability and satisfaction when users search for content such as "event" and "taste restaurant." Reliability shows the number of ad posts on a blog, the total number of posts, and satisfaction shows a clean post with confidence divided into positive and negative posts. Finally, the keyword shows a list of the top three words in the review from a positive post. In this way, it helps users interpret information away from advertising.

• The Optical Journal
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• s.145
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• pp.47-50
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• 2013

Reed Exhibitions Japan이 주최하는 일본 최대의 광 레이저 종합 기술 전시회 'Photonix 2013'이 지난 4월 10일부터 12일까지 사흘간 도쿄 빅사이트 전시장에서 성황리에 개최됐다. 이번 전시회는 전 세계에서 광 레이저 관련 첨단 제품과 기술이 한데 집결한 가운데 진행돼 수많은 광학 업계 종사자들을 불러 모았다.

• Digital Contents
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• no.9 s.124
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• pp.116-119
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• 2003

IT시대와는 전혀 상관없어 보이는 보드게임이 의외로 뜨고 있다. 컴퓨터 없이는 좌불안석하는 현대의 젊은이들이 종이 조각을 교환하고 자그마한 주사위 등을 굴리며 즐기고 있다. 컴퓨터와의 게임에 지쳐서일까? 사람의 호흡이 그리워서일까? 하여튼 많은 사람들이 보드게임을 즐기게 되었고, 그 수요 역시 확산되고 있다. 이번 모바일 리뷰에서는 모바일에서 구현되는 특색 잇는 보드게임 2종을 소개하고자 한다. '정반합'이라고 하지 않았던가?

• Korean Architects
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• s.495
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• pp.44-51
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• 2010

안우성 건축사는 착실히 기본기를 다진 건축사로 보여졌다. 그의 수련 과정과 관심분야를 보면 매우 견고한 과정을 거쳤고, 실용적인 설계에 능함을 알 수 있었다. 현재의 안건축사와 온고당은 그런 기반 하에 자리잡을 것으로 여겨졌다. 지금도 매우 다양한 프로젝트와 다양한 분야에서 활동하고 있는데, 앞으로의 활동이 더욱 기대된다 하겠다. 앞으로도 더욱 좋은 건축을 많이 하길 기대한다.

• Vending industry
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• v.1 no.4 s.4
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• pp.80-82
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• 2002

현금이 없어도 자판기를 사용할 수 있는 시대가 도래했다. 국내 카드 & 폰빌링 결제시스템의 기술발달은 앞으로 빠른 속도로 현금결제시스템을 대체해 갈 것으로 보여진다. 금호 기술리뷰에서도 삼성광주전자 개발팀의 협조를 받아 카드 & 폰빌링 시스템이 어떠한 시스템원리와 동작으로 자판기를 통해 상용화되는 지를 알아보는 시간을 마련했다.

• Journal of the Korea Society of Computer and Information
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• v.25 no.6
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• pp.81-89
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• 2020

Online reviews we encounter commonly on SNS, although a complex range of assessment information affecting the consumer's preferences are included, it is general that such information is just provided by simple numbers or star ratings. Based on those review types, it is not easy to get specific information that consumers want and use it to make a decision for purchase. Therefore, in this study, we propose a prediction methodology that can provide ratings broken down by evaluation items by performing sentiment analysis on restaurant reviews written in Korean. To this end, we select 'food', 'price', 'service', and 'atmosphere' as the main evaluation items of restaurants, and build a new sentiment dictionary for each evaluation item. It also classifies review sentences by rating item, predicts granular ratings through sentiment analysis, and provides additional information that consumers can use to make decisions. Finally, using MAE and RMSE as evaluation indicators it shows that the rating prediction accuracy of the proposed methodology has been improved than previous studies and presents the use case of proposed methodology.

• Journal of the Korean Society for information Management
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• v.39 no.3
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• pp.311-336
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• 2022

This study analyzed the contents of Goodreads review data, which is a social cataloging service with the participation of book users around the world, to identify the preference factors that affect book users' book recommendations in the library information service environment. To understand user preferences from a more detailed point of view, sub-datasets for each rating group, each book, and each user were constructed in the sample selection process. Stratified sampling was also performed based on the result of topic modeling of review text data to include various topics. As a result, a total of 90 preference factors belonging to 7 categories('Content', 'Character', 'Writing', 'Reading', 'Author', 'Story', 'Form') were identified. Also, the general preference factors revealed according to the ratings, as well as the patterns of preference factors revealed in books and users with clear likes and dislikes were identified. The results of this study are expected to contribute to more sophisticated recommendations in future recommendation systems by identifying specific aspects of user preference factors.

• Journal of Intelligence and Information Systems
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• v.22 no.3
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• pp.23-43
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• 2016

As a result of the growth of Internet data and the rapid development of Internet technology, "big data" analysis has gained prominence as a major approach for evaluating and mining enormous data for various purposes. Especially, in recent years, people tend to share their experiences related to their leisure activities while also reviewing others' inputs concerning their activities. Therefore, by referring to others' leisure activity-related experiences, they are able to gather information that might guarantee them better leisure activities in the future. This phenomenon has appeared throughout many aspects of leisure activities such as movies, traveling, accommodation, and dining. Apart from blogs and social networking sites, many other websites provide a wealth of information related to leisure activities. Most of these websites provide information of each product in various formats depending on different purposes and perspectives. Generally, most of the websites provide the average ratings and detailed reviews of users who actually used products/services, and these ratings and reviews can actually support the decision of potential customers in purchasing the same products/services. However, the existing websites offering information on leisure activities only provide the rating and review based on one stage of a set of evaluation criteria. Therefore, to identify the main issue for each evaluation criterion as well as the characteristics of specific elements comprising each criterion, users have to read a large number of reviews. In particular, as most of the users search for the characteristics of the detailed elements for one or more specific evaluation criteria based on their priorities, they must spend a great deal of time and effort to obtain the desired information by reading more reviews and understanding the contents of such reviews. Although some websites break down the evaluation criteria and direct the user to input their reviews according to different levels of criteria, there exist excessive amounts of input sections that make the whole process inconvenient for the users. Further, problems may arise if a user does not follow the instructions for the input sections or fill in the wrong input sections. Finally, treating the evaluation criteria breakdown as a realistic alternative is difficult, because identifying all the detailed criteria for each evaluation criterion is a challenging task. For example, if a review about a certain hotel has been written, people tend to only write one-stage reviews for various components such as accessibility, rooms, services, or food. These might be the reviews for most frequently asked questions, such as distance between the nearest subway station or condition of the bathroom, but they still lack detailed information for these questions. In addition, in case a breakdown of the evaluation criteria was provided along with various input sections, the user might only fill in the evaluation criterion for accessibility or fill in the wrong information such as information regarding rooms in the evaluation criteria for accessibility. Thus, the reliability of the segmented review will be greatly reduced. In this study, we propose an approach to overcome the limitations of the existing leisure activity information websites, namely, (1) the reliability of reviews for each evaluation criteria and (2) the difficulty of identifying the detailed contents that make up the evaluation criteria. In our proposed methodology, we first identify the review content and construct the lexicon for each evaluation criterion by using the terms that are frequently used for each criterion. Next, the sentences in the review documents containing the terms in the constructed lexicon are decomposed into review units, which are then reconstructed by using the evaluation criteria. Finally, the issues of the constructed review units by evaluation criteria are derived and the summary results are provided. Apart from the derived issues, the review units are also provided. Therefore, this approach aims to help users save on time and effort, because they will only be reading the relevant information they need for each evaluation criterion rather than go through the entire text of review. Our proposed methodology is based on the topic modeling, which is being actively used in text analysis. The review is decomposed into sentence units rather than considering the whole review as a document unit. After being decomposed into individual review units, the review units are reorganized according to each evaluation criterion and then used in the subsequent analysis. This work largely differs from the existing topic modeling-based studies. In this paper, we collected 423 reviews from hotel information websites and decomposed these reviews into 4,860 review units. We then reorganized the review units according to six different evaluation criteria. By applying these review units in our methodology, the analysis results can be introduced, and the utility of proposed methodology can be demonstrated.