• Journal of the Korean Geographical Society
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• v.38 no.2
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• pp.275-291
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• 2003

It was essential to develop the DB-type teaching and teaming material for geography instruction using a method of ICT. The DB-type teaching and learning material was considered as a alternative in solving the problems of web-based geography instruction. Accordingly, in this study, the geography image DB program as developed, and based on this program the CD-ROM called GEO-DB, having the function of electronic dictionary of geography image for geography teaching and teaming was made. The GEO-DB was composed of 3,060 geography images collected by teachers and learners. The GEO-DB was made to be used simply by teachers and learners. Especially, the portfolio function was Included in the GEO-DB, and that was focused to the instructional system design of teacher and the self-directed teaming ability development of learner. Teachers and learners using this GEO-DB assessed that because the GEO-DB had the easiness of use, the speed of reference and the unlimitedness of extension, it could enlarge the possibility of using a method of In, and it could contribute to the development of geography teaming ability and the change of geography teaming attitude.

• Journal of Korean Library and Information Science Society
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• v.53 no.2
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• pp.165-188
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• 2022

The purpose of this research is to document the current state of 'One Book, One City' community reading campaign (Hereafter called 'One Book' reading campaign), launched in 2003 in Korea, and the characteristics of the selected books. For this research, the homepages, news and reports of a total of 1,170 public libraries and their local government, and several major institutions and organizations related to reading and culture were analyzed with the research method of content analysis and literature review. Also, online catalogs of the National Library of Korea and the National Library for Children and Young Adults were examined to identify the characteristics of 729 titles and 1,179 volumes of books selected in 57 'One Book' programs, as of 2021. The analysis of 57 'One Book' programs and those selected books shows the selection of more than one books in different age groups in more and more 'One Book' programs, lack of consistency in themes of those selected books, and preference for young adult books, new publications and bestselling novels. This trend has weakened individual 'One Book' programs' concentration on one book or one subject, but helped invite a diverse group of people with various interests. More in-depth analysis and explanation of the process of book selection and its appropriateness with the stated goals of 'One Book' programs are needed.

• Archives of design research
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• v.18 no.4 s.62
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• pp.25-34
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• 2005

The purpose of the present study is to investigate the characteristics of the current Victorian-style interior by reviewing the basic Victorian-style house in the past. this research was analyzed various prior studies and literatures, and found the following results: First, the Victorian-style house and interior space showed various historical trends and adopted every style from Gothic to rococo, and sometimes more than one style influenced a single place. Its formality was applied depending on the function and standard of each room. Second, the interior had many decorative things with free, irregular or other patterns, influenced by Romanticism and Naturalism. The several environmental factors such as air pollution and hygienic matter were also related with its trend. the dramatic changes in the kitchen and sanitary facilities were appeared based on the technical development, and affluent design styles were also used. All these reflected the characteristics of the Victorian age. In conclusion, the characteristics of Victorian-style were influenced by many factors including: (a) the trend of Romanticism and Naturalism, (b) consideration of family convenience based on the technical development, (c) the Socio-Environmental factors like air pollution and the social norm, and (d) reflection of the individual value in accordance with frequent contacts with foreign cultures. In this respect, it is necessary to reevaluate the Victorian-style after paying due regard to such factors.

• Korean journal of communication and information
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• v.16
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• pp.71-107
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• 2001

미국에서 이루어진 인터넷 중독 현상에 대한 초기 연구는 인터넷 중독을 알코올중독과 같은 개인의 정신적 질병으로 간주하는 의사들에 의해 주도되었다. 그러나 사회현상으로서 인터넷 중독에 대한 사회과학자들의 관심이 증대되면서 인터넷 중독의 원인을 밝히는 본격적인 연구가 이루어진다. 인터넷 이용과 초고속 인터넷 망 보급속도에서 세계최고 수준을 자랑하는 우리의 경우에도 인터넷 이용에 따른 많은 부정적인 현상들이 나타남으로써 사회적인 문제로 대두되고 있다. 이에 따라 인터넷 중독에 대한 일부 연구가 수행되었는데 이들 연구들은 인터넷 이용패턴과 이용동기를 개별적으로 분석하고 인터넷 중독정도를 측정하는 차원에 머물고 있다. 즉, 인터넷 중독의 원인을 분석하는 차원에 이르지 못하고 있다. 또한 대부분의 연구들이 10대 청소년을 연구대상으로 하고 있기 때문에 다른 연령층의 인터넷 이용특성을 파악하는 데 한계를 가지고 있다. 이 같은 현실 인식을 바탕으로 본 연구는 2000년에 발표된 한국전산원 통계수치에서 인터넷을 가장 많이 이용하는 집단으로 조사된 대학생들을 연구대상으로, (1) 이들의 인터넷 이용패턴과 이용동기를 밝히고 (2) 이들 변인들과 인터넷 중독과의 상호관련성을 분석하며 (3) 인터넷 중독의 정도와 중독요인을 조사하고 (4) 마지막으로 인터넷 이용이 다른 미디어 이용과 면대면 커뮤니케이션에 미치는 영향을 분석하고 있다. 본 연구의 자료는 2000년 5월 8일부터 19일까지 2주간에 걸쳐 서울시내 대학생들을 대상으로 강의시간에 설문지를 배포하고 응답자가 설문지에 답하는 방법을 통해 수집되었다. 수집된 556명의 설문지 가운데 유효한 512명의 설문지가 통계적인 방법을 통해 분석되었다. 설문지는 (1) 인터넷 이용패턴 (2) 인터넷 이용 동기 (3) 인터넷 의존도 (4) 인터넷 이용 이후 다른 미디어 이용정도 (5) 인터넷 이용 이후 면대면 커뮤니케이션 정도 (6) 인구통계학적 변인을 측정하는 질문 내용으로 구성되었다. 통계 분석 후 나타난 몇 가지 주요결과를 요약하면 아래와 같다. (1) 이용동기와 인터넷 이용과의 상호관련성 이용동기를 요인 분석한 결과, 6개의 이용동기가 나타났는데 오락이 가장 주요한 동기였으며 다음으로 교육/정보, 현실도피, 외로움, 쇼핑, 그리고 성적 만족 순으로 나타났다. 이용 동기들을 인터넷 이용시간과의 상호관련성을 통계 분석한 결과 기존 연구결과와 달리 성적 만족이 6가지 요인 가운데 가장 낮은 상호관련성을 보였다. 또한 이용동기 분석에서 두 번째 높게 나타난 교육/정보 역시 성적 만족 다음으로 낮은 상호관련성을 보여주었다. 이는 대학생들의 인터넷 이용이 10대들의 인터넷 이용형태와 상당히 다르다는 것을 보여주는 것으로 본 연구에서는 수행하지 못한 이 같은 결과가 나오게 된 이유를 밝히는 후속연구가 필요할 것으로 보인다. (2) 인터넷 이용동기와 인터넷 서비스와의 상호관련성 '오락은 게임, 토론그룹, 전자메일, 채팅과 상호관련을 가진 것으로 나타났으며, 교육/정보는 검색과 쇼핑, 현실도피는 게임과 토론그룹, 외로움은 토론그룹, 전자메일과 채팅, 쇼핑은 온라인 쇼핑과 상호관련성이 있는 것으로 분석되었다. 흥미로운 사실은 성적 만족과 관련해서 게임과 채팅은 긍정적인 상호관련을 가진 것으로 나타난 반면 전자메일 서비스 이용은 성적 만족과 부정적인 상호관련을 가진 것으로 분석되었다. 이는 대학생들이 지루하게 느끼거나 외로움을 느낄 때 전자메일을 주로 이용하지만 성적 만족을 위해 전자메일을 이용하지 않고 있다는 사실을 보여주는 것이다. (3) 인터넷 이용 이후 다른 미디어와 면대면 커뮤니케이션과의 관계 인터넷을 이용한 후 응답자들의 전통적인 미디어(텔레비전, 라디오, 신문, 잡지, 편지, 전화) 이용이 감소되었으며 친구, 가족, 이성친구와의 면대면 커뮤니케이션 역시 감소된 것으로 나타났는데 이 같은 감소가 인터넷 이용과 관련이 있는 것으로 나타났다. (4) 인터넷 중독 정도와 중독 요인 10대들을 대상으로 한 기존 연구에서 나타난 인터넷 중독 현상이 대학생 집단에서는 나타나지 않았다. 그러나 응답자의 28.5%가 중독집단으로 발전될 가능성을 가진 잠재적인 인터넷 의존자(Moderate Internet Dependent)로 조사되었다. 인터넷 중독을 설명하는 요인으로 이용동기 가운데 오락, 외로움과 현실도피가 주요 변인으로 나타났으며 인터넷 이용시간 역시 주요변인으로 분석되었다. 흥미 있는 결과는 선행연구에서 인터넷 중독과 밀접한 관련 있는 인터넷 서비스로 조사된 게임과 채팅이 주요변인으로 나타나지 않았다는 것이다. 또한 인터넷 이용동기와 이용시간과의 상호관련 조사 결과에서처럼 전자메일서비스는 인터넷 중독과 부정적인 관계가 있는 것으로 조사되었다.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.85-109
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• 2018

Recommender system recommends the items expected to be purchased by a customer in the future according to his or her previous purchase behaviors. It has been served as a tool for realizing one-to-one personalization for an e-commerce service company. Traditional recommender systems, especially the recommender systems based on collaborative filtering (CF), which is the most popular recommendation algorithm in both academy and industry, are designed to generate the items list for recommendation by using 'overall rating' - a single criterion. However, it has critical limitations in understanding the customers' preferences in detail. Recently, to mitigate these limitations, some leading e-commerce companies have begun to get feedback from their customers in a form of 'multicritera ratings'. Multicriteria ratings enable the companies to understand their customers' preferences from the multidimensional viewpoints. Moreover, it is easy to handle and analyze the multidimensional ratings because they are quantitative. But, the recommendation using multicritera ratings also has limitation that it may omit detail information on a user's preference because it only considers three-to-five predetermined criteria in most cases. Under this background, this study proposes a novel hybrid recommendation system, which selectively uses the results from 'traditional CF' and 'CF using multicriteria ratings'. Our proposed system is based on the premise that some people have holistic preference scheme, whereas others have composite preference scheme. Thus, our system is designed to use traditional CF using overall rating for the users with holistic preference, and to use CF using multicriteria ratings for the users with composite preference. To validate the usefulness of the proposed system, we applied it to a real-world dataset regarding the recommendation for POI (point-of-interests). Providing personalized POI recommendation is getting more attentions as the popularity of the location-based services such as Yelp and Foursquare increases. The dataset was collected from university students via a Web-based online survey system. Using the survey system, we collected the overall ratings as well as the ratings for each criterion for 48 POIs that are located near K university in Seoul, South Korea. The criteria include 'food or taste', 'price' and 'service or mood'. As a result, we obtain 2,878 valid ratings from 112 users. Among 48 items, 38 items (80%) are used as training dataset, and the remaining 10 items (20%) are used as validation dataset. To examine the effectiveness of the proposed system (i.e. hybrid selective model), we compared its performance to the performances of two comparison models - the traditional CF and the CF with multicriteria ratings. The performances of recommender systems were evaluated by using two metrics - average MAE(mean absolute error) and precision-in-top-N. Precision-in-top-N represents the percentage of truly high overall ratings among those that the model predicted would be the N most relevant items for each user. The experimental system was developed using Microsoft Visual Basic for Applications (VBA). The experimental results showed that our proposed system (avg. MAE = 0.584) outperformed traditional CF (avg. MAE = 0.591) as well as multicriteria CF (avg. AVE = 0.608). We also found that multicriteria CF showed worse performance compared to traditional CF in our data set, which is contradictory to the results in the most previous studies. This result supports the premise of our study that people have two different types of preference schemes - holistic and composite. Besides MAE, the proposed system outperformed all the comparison models in precision-in-top-3, precision-in-top-5, and precision-in-top-7. The results from the paired samples t-test presented that our proposed system outperformed traditional CF with 10% statistical significance level, and multicriteria CF with 1% statistical significance level from the perspective of average MAE. The proposed system sheds light on how to understand and utilize user's preference schemes in recommender systems domain.

• 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