• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.167-175
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• 2024

Due to the Fourth Industrial Revolution, ICT(Information and Communication Technology) industry is becoming more important and sophisticated than ever. In B2B based ICT industry demand forecasting by analyzing the previous customer data is so important. RFM, one of customer relationship management models is a marketing technique that evaluates Recency, Frequency and Monetary value to predict customers behavior. RFM model has been studied focusing on the B2C based industry. On the other hand there is a lack of research on B2B based technology industry. Therefore this study applied it to B2B based high technology industry and considered T(technology collaboration) value, which are identified as important factors in the technology industry. To present an improved model for market performance in B2B technology industry, an empirical study was conducted on comparing the accuracy of the traditional RFM model and the improved RFM-T model. The objective of this study is to contribute to market performance by presenting an improved model in B2B based high technology industry.

• 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.

• Journal of the Korean Institute of Landscape Architecture
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• v.36 no.6
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• pp.81-90
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• 2009

This study seeks those elements that form a sense of place in Yen-Ben Street, which represents a typical ethnic enclave in Seoul, to provide a basic resource in the creation of an urban landscape that can provide a positive space for cultural diversity. The results of the study can be summarized as follows: First, the element of a physical environment that develops a sense of place was in fact the poor dwellings that correspond to the economic condition of Korean Chinese. While this element has a negative cognition to outsiders, Korean Chinese feel positively toward it. Secondly, signboards were a physical element of sense of place which retains cultural identity as a means of communication inside the community. Thirdly, it was found that activities such as shopping, recreation, and the exchange of information that are found in the pursuit of daily life act as an essential element in the formation of a sense of place even more than architectural elements. Fourthly, the appropriation of space by Korean Chinese and the isolation from the surroundings were obvious. This isolation is perceived as a negative sense of place formation to outsiders in Yen-Ben Street. Fifthly, the aspects of cultural dualism, mingling the concepts of home country, language, writing, and food have also affected the formation of a sense of place in the area. Sixthly, transience was a prominent phenomenon of Yen-Ben Street and is strengthened by illegal immigration. Although transience causes negative impacts such as in a lack of concern for the residential environment, it acts as a positive factor in the sense of place by mitigating uneasiness, and strengthening insider ties and cooperation.

• Korean journal of food and cookery science
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• v.27 no.3
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• pp.11-20
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• 2011

The purpose of this study was to investigate the use and perception of adults concerning bokbunja (Rubus coreanus Miquel) products. Self-administered questionnaires were collected from 502 residents in the Daegu and Gyeongbuk area. According to the survey more females in their 20s responded than males (45.2 and 54.8%, respectively). In total, 82.6% of respondents had an income of under 4,000,000 won per month and most were living in the city. The results regarding knowledge about bokbunja products showed that the bokbunja wine score was highest (3.66), and intake frequency showed that over half of the respondents had never eaten bokbunja products. The preference for bokbunja wine by males was higher than that for females, whereas the others products showed higher scores for females than for males. When asked about how they knew about bokbunja products, 37.0% of males and 46.9% of females responded a family member or neighbor. When purchasing bokbunja products, males and females answered that they considered taste, country of origin, and manufacturer, and price. Approximately 48% of the respondents answered that they purchased bokbunja products in the grocery and department store. As a result, popularization of bokbunja products was based on product development and sales promotion, and the product development factor significantly influenced preference for bokbunja products.

• The Bulletin of The Korean Astronomical Society
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• v.46 no.2
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• pp.73.4-74
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• 2021

한국천문연구원은 2017년 제1차 구술채록사업에 이어 2020년 제2차 사업을 진행하면서 최초로 원외 원로에 대한 구술채록을 시도하였다. 국가 대표 천문연구의 산실로서 연구원 존재 의의를 확립하기 위하여 원내 원로에 국한되었던 구술자 대상을 확장한 것이다. 그 첫 외부 구술 대상자로 방득룡 전임 노스웨스턴 천문학과 교수를 선정하여 2020년 7월부터 준비단계에 들어갔다. 방득룡 전(前)교수가 첫 번째 한국천문연구원 원외 인사 구술자로 선정된 이유는, 그가 우리나라 천문대1호 망원경 구매 선정에 개입한 서신(1972년)이 자료로 남아있었기 때문이다. 한국천문연구원에서 2017년에 수행한 제1차 구술채록사업에서 구술자로 참여한 오병렬 한국천문연구원 원로가 기증한 사료들은 대부분 연구원 태동기 국립천문대 구축과 망원경 구매 관련 자료였으며 이 가운데 1972년 당시 과학기술처 김선길 진흥국장에게 Boller and Chivesns(사(社))의 반사경을 추천한 방득룡 전(前)교수의 서신은 한국 천문학 발전사에서 중요한 사료였다. 연구진은 이 자료를 시작으로, 방득룡 전(前)교수의 생존 여부와 문서고의 공기록물들에서 그의 흔적을 찾아가기 시작했다. 놀랍게도 그는 실제 세계와 한국천문연구원 문서고 깊숙이 기록물들 모두에서 상존하고 있었다. 1927년생인 방득룡 전(前)교수, Dr. John D. R.은 미국 플로리다 한 실버타운에서 건강한 정신으로 생존하여 있었고 연구진의 인터뷰에 흔쾌히 응했다. 2020년 9월 16일에 한국천문연구원 본원 세종홀 2층 회의실에서 영상통신회의로 그와의 구술인터뷰가 진행되었다. 이 구술인터뷰는 원외 인사가 대상이란 점 외에도 방법적으로는 전형적인 대면 방식이 아닌 영상 인터뷰였다는 점에서 코로나 시대의 대안이 되는 실험적 시도였다. 현대 한국천문학 발전사의 재조명 측면에서도 의미가 있었다. 1960년대 초반부터 1992년 정년퇴임까지 30년을 미국 유수 대학교 천문학과 교수로 재직하며 활발한 활동을 해 온 한국계 천문학자가 우리나라 최초 반사망원경 구매 선정에 적극 개입하였던 역사는, 공문서 자료들과 서신 사료들에 이어 그의 육성으로 나머지 의구심의 간극이 채워졌다. 또 구술자 개인이 주관적으로 중요하다고 여기는 '기억'이 중요한 아카이빙 콘텐츠 확장의 단초가 될 수 있다는 것을 보여줌으로써 구술사 연구에 있어서도 중요한 관점을 주었다. 애초 연구진이 방득룡 전(前)교수의 공식 기록에서 아카이빙의 큰 줄기로 잡았던 것은 1948년 도미, 1957년 위스콘신 대학교 천문학 박사학위 취득, 1962년부터 노스웨스턴 대학(일리노이주 에반스턴)의 천문학 교수진, 1992년 은퇴로 이어진 생애였다. 그러나 그와의 구술 준비 서신 왕래와 구술을 통하여 알게 된 그가 인생에서 중요시 여겼던 지점은, 1948년 도미 무렵 한국의 전쟁 전 상황과 당시 비슷한 시기에 유학한 한국 천문학자들의 동태, 그리고 1957년부터 1962년까지 프린스턴 대학교에서 M. Schwarzschild 교수와 L. Spitzer 교수를 보조하며 Stratoscope Project를 연구하였던 경험이었다. 기록학적 의미에서도, 전자를 통해서 그와 함께 동시대 한국 천문학을 이끌었던 인재들의 맥락정보를 얻을 수 있었으며, 후자를 통해서는 세계 천문학사에 큰 영향을 미친 석학에 대한 아카이브 정보와의 연계 지점과 방득룡 전(前)교수의 연구 근원을 찾을 수 있었다. 이들은 추후 방득룡 콘텐츠 서비스 시에 AIP, NASM, Lyman Spitzer 콘텐츠, 평양천문대, 화천조경천문대, 서울대와 연세대, 그리고 한국천문연구원까지 연계되어 전 세계 폭넓은 이용자들의 유입을 유도할 수 있는 검색 도구가 될 수 있다. 이번 방득룡 구술사 연구에서 구술자 개인의 주관적인 소회가 공식 기록이 다가갈 수 없는 역사적 실체에 일정 부분 가까울 수 있다는 것, 그리고 이를 통하여 개인의 역사는 공동체의 역사로 확장될 수 있다는 사실을 발견할 수 있었다. 또 연구진은 방득룡 전(前)교수의 회상을 통하여 구술자 개인의 시각으로 한국과 미국 천문학계의 공동체 역사를 재조명할 수 있었고, 이것을 아카이브 콘텐츠 확장 서비스에 반영할 수 있다는 기대를 가지게 되었다. 무엇보다 이 연구를 통하여 다양한 주제의 아카이브로 연동될 수 있는 주제어와 검색도구를 구술자 개인의 회상으로부터 유효하게 도출할 수 있다는 것을 확인하였다. 그리고 향후 한국천문 구술아카이브의 확장을 통하여 보다 다양한 활용과 연구 재활용의 선순환이 가능하다는 것도 알 수 있었다. 이는 최근 기록학계에서 대두되고 있는 LOD(Linked Open Data)의 방향성과도 흡사하여 한국천문학 구술사연구의 차세대 통합형 기록관리의 미래모형을 기대케 하는 대목이다.

• Cartoon and Animation Studies
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• s.27
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• pp.51-78
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• 2012

The types of cartoon market are classified with publishing cartoon(a cartoon magazine & comics) and webtoon. The revitalization of the cartoon market makes cartoonist create many cartoons. By studying many methods for the revitalization of the cartoon market, this paper argues the expanded methods of comics market which is a sort of publishing cartoon market. The expanded methods of comics market are two kinds, one is the revitalization of the comics market and the other is the creation of the comics market. This paper focuses on Genre-mixed Knowledge-Cartoon in order to extend the cartoon market. Also, After studying the Creation Proceed of cartoon market through Genre-mixed Knowledge-Cartoon, we would like to develope the New Creation Model of Cartoon Market. We selected three case(the Real Estate Agency expressed as Cartoon, Let's find an answer in sided figure blank, miraculous English grammar) for this study. With this, we analyzed the case that the matters for analysis is the essential particulars of plan-publishing-distribution's proceed. As a result, we found out the possibility of new cartoon market's creation through Genre-mixed Knowledge-Cartoon. For that reason, we was able to develop 'the New Creation Model of Cartoon Market through Genre-mixed Knowledge-Cartoon'. This paper provides the possibility about the New Creation Model of Cartoon Market through Genre-mixed Knowledge-Cartoon. With this, we will make many plans for creation of Genre-mixed Knowledge-Cartoons. Therefore, This plans will help cartoonists to create the Genre-mixed cartoons.

• Korean Journal of Construction Engineering and Management
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• v.6 no.2 s.24
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• pp.120-128
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• 2005

ISO 9001, the quality management system issued by the International Organization for Standardization, is being used by architectural design and engineering firms in order to strengthen the capability of business activities through the implementation of the international and advanced quality management systems. However, there have been significant problems in stable implementation and settlement of ISO 9001 in construction industry, which seem to be caused by key employees' lack of proper recognition and comprehension. The purpose of this research, accordingly, is to find and analyze nonconformity results which were found when the third party registrars audited the conformity of companies' quality management systems for ISO 9001 certification especially in architectural design and engineering firms. For this purpose this research was conducted by a cluster analysis of 647 audit reports out of representative 15 architectural design and engineering firms that have been audited periodically from 1997 to 2003 by the third party registrars. The analysis showed that the most frequent problems were generated in the areas of $\ulcorner$Design and Development$\lrcorner$ , $\ulcorner$production and Service Provision$\lrcorner$ , and $\ulcorner$General requirements$\lrcorner$ of the quality management system. The following, the areas of $\ulcorner$Monitoring and Measurement$\lrcorner$ and $\ulcorner$purchasing$\lrcorner$ were also analyzed as main factors which caused frequent nonconformity results. This research also shows that the corrective actions for nonconformity results are closely connected with the whole management activities in architectural design and engineering firms. Consequently, corrective actions for disposition of nonconformities should be implemented more specifically in order to settle and activate the quality management systems in architectural design and engineering firms.

• Journal of the Korean Institute of Landscape Architecture
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• v.47 no.4
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• pp.33-49
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• 2019

The purpose of this study was to investigate the changes in the experiences of visitors of Yeonnam-dong during the period covering the development of a linear park, the Gyeongui Line Park. This study used a text mining technique to analyze Naver Blog postings of those who visited Yeonnam-dong from June 2013 to May 2017, divided into four periods -from June 2013 to May 2014, from June 2014 to May 2015, from June 2015 to May 2016 and from June 2016 to May 2017. The keywords used were 'Yeonnam-dong', 'Gyeongui Line' and 'Yeontral Park' and the data was further refined and resampled. A semantic network analysis was conducted on the basis of the co-occurrences of words. The results of the study were as follows. During the entire period, the main experience of visitors to Yeonnam-dong was 'food culture' consistently, but the activities related to 'market', 'browsing', and 'buy' increased. Also, activities such as 'walk', 'play' and 'rest' in the park newly appeared after the construction of the park. Moreover, more diverse opinions about the Yeonnam-dong were expressed on the blog, and Yeonnam-dong began to be recognized as a place where a variety of activities can be enjoyed. Lastly, when the visitors wrote about the theme 'food culture', the scope of the keywords expanded from simple ones, such as 'eat', 'photograph' and 'chatting' to 'market', 'browsing', and 'walk'. The sub-themes that appeared with the park also expanded to various topics with the emergence of the Gyeongui Line Book Street. This study analyzed the change of experiences of visitors objectively with text mining, a quantitative methodology. Due to the nature of text mining, however, the subjective opinions inevitably have been involved in the process of refining. Also, further research is required to assess the direct relationship between these changes and park construction.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.137-148
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• 2014

Recommender system has become one of the most important technologies in e-commerce in these days. The ultimate reason to shop online, for many consumers, is to reduce the efforts for information search and purchase. Recommender system is a key technology to serve these needs. Many of the past studies about recommender systems have been devoted to developing and improving recommendation algorithms and collaborative filtering (CF) is known to be the most successful one. Despite its success, however, CF has several shortcomings such as cold-start, sparsity, gray sheep problems. In order to be able to generate recommendations, ordinary CF algorithms require evaluations or preference information directly from users. For new users who do not have any evaluations or preference information, therefore, CF cannot come up with recommendations (Cold-star problem). As the numbers of products and customers increase, the scale of the data increases exponentially and most of the data cells are empty. This sparse dataset makes computation for recommendation extremely hard (Sparsity problem). Since CF is based on the assumption that there are groups of users sharing common preferences or tastes, CF becomes inaccurate if there are many users with rare and unique tastes (Gray sheep problem). This study proposes a new algorithm that utilizes Social Network Analysis (SNA) techniques to resolve the gray sheep problem. We utilize 'degree centrality' in SNA to identify users with unique preferences (gray sheep). Degree centrality in SNA refers to the number of direct links to and from a node. In a network of users who are connected through common preferences or tastes, those with unique tastes have fewer links to other users (nodes) and they are isolated from other users. Therefore, gray sheep can be identified by calculating degree centrality of each node. We divide the dataset into two, gray sheep and others, based on the degree centrality of the users. Then, different similarity measures and recommendation methods are applied to these two datasets. More detail algorithm is as follows: Step 1: Convert the initial data which is a two-mode network (user to item) into an one-mode network (user to user). Step 2: Calculate degree centrality of each node and separate those nodes having degree centrality values lower than the pre-set threshold. The threshold value is determined by simulations such that the accuracy of CF for the remaining dataset is maximized. Step 3: Ordinary CF algorithm is applied to the remaining dataset. Step 4: Since the separated dataset consist of users with unique tastes, an ordinary CF algorithm cannot generate recommendations for them. A 'popular item' method is used to generate recommendations for these users. The F measures of the two datasets are weighted by the numbers of nodes and summed to be used as the final performance metric. In order to test performance improvement by this new algorithm, an empirical study was conducted using a publically available dataset - the MovieLens data by GroupLens research team. We used 100,000 evaluations by 943 users on 1,682 movies. The proposed algorithm was compared with an ordinary CF algorithm utilizing 'Best-N-neighbors' and 'Cosine' similarity method. The empirical results show that F measure was improved about 11% on average when the proposed algorithm was used