• International Journal of Knowledge Content Development & Technology
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• v.10 no.3
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• pp.69-86
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• 2020

As the South Korean government has recently announced its intention to implement a three-year policy on building additional libraries and complex community centers as the community-based everyday life SOC project, society has shed new light on libraries as public service institutions. Accordingly, this study was conducted to determine the factors affecting resident satisfaction with public libraries, intention to use, and intention to recommend public libraries, for use as basic data to increase resident satisfaction and use of public libraries in South Korea. To this end, we conducted a survey on residents who have experience with using 13 public libraries designated as regional representative libraries in South Korea. The surveyed data was verified with a structural equation using AMOS. The results were as follows. First, all factors, such as material, facility, staff, program, and service, except location and space, had a significant effect on resident satisfaction with public libraries. Second, it was found that satisfaction had a significant effect on the intention to use and intention to recommend. The results of this study may contribute to qualitatively improving public library services by reflecting the changing needs of users, as well as social trends at the working level of libraries in South Korean society.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3550-3565
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• 2019

This paper proposes a new measurement method for the effective measurement of the 99% occupied bandwidth (OBW) at monitoring stations. Although the OBW measurement of radio signal is recommended by the International Telecommunication Union Radio (ITU-R) with several methods, there still does not exist a clear measurement recommendation or standard for terrestrial DTV signal on-air environment. Modified adjacent channel power ratio (MACPR), which can be applied to 8-VSB (Vestigial Side Band) DTV (Digital Television) signal, is herein defined to verify the results of measurements obtained using the proposed measurement method. MACPR is a proper measuring parameter for determining the measuring area of a monitoring station. From measurement results obtained in real field environment, it has been found that the OBW of 8-VSB DTV signal can be effectively measured in areas where the MACPR value is over 35 dB and when the measurements are repeated more than 600 times in the same reception site. It also has been verified that measured results are within an error range of +/-0.1% compared to results directly obtained at a transmission station. It is expected that the proposed method is able to be employed in order to determine the proper location of monitoring station and provide a reliable OBW measurement procedure for 8-VSB DTV signal on-air environment.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.365-367
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• 2022

본 논문에서는 서울시를 대상으로 2020년 기준 자치구별 공공체육시설의 개수를 분석하고, 도출된 서비스 지역 적정 개소 수를 기준으로 추가 설치가 필요한 자치구 내 입지를 예측하였다. 기존 공공 체육시설 수와 선행연구의 입지 지표를 활용해 회귀분석을 바탕으로 유의한 입지요인을 도출하고, 이를 변수로 한 k-means 군집화를 통해 자치구별 입지 후보군이 될만한 행정구역상 동을 구분하였다. 이후 선정된 행정구역 내 기준 인구 당 공공체육시설 비율이 같아지도록 공공체육시설 설치 개수를 결정한 다음 각 구역의 중심점으로부터 가까운 동 순으로 공공체육시설의 추가 설치가 필요한 동을 선정하였다.

• 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 the Korean Association of Geographic Information Studies
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• v.15 no.3
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• pp.23-35
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• 2012

The optimum location of the prehistoric sites of Ulsan Metropolitan City are investigated by both quantile and natural breaks methods through GIS, and the settlement pattern is studied based on the possibility of presence of the prehistoric sites which are also analyzed with these methods. Such factors including elevation, slope, distance from the nearest water, aspect, geological features, soil drainage classes, subsoil and land use recommended are employed in the analysis. The optimum geographical environment is the place where it includes the water-base in the area that is the southern aspect of the gentle slope land of lowland. The geology is the Quaternary alluvium. The drainage class is fine and the deep soil saturn is the fine loamy soil and the recommendation of land use is the area that is the field. As a result of the forecast of distribution, the prehistoric sites showed the higher possibility of presence in the downstream region where the Taehwa river and Dongcheon river join because the region come close to the watercourse and the drinking water use is easy. And the aspect and elevation is the low area. The alluvium accumulated from the upper stream of the Taehwa river and Dongheon river was made roomily, the area where is suitable for the farming life. Therefore, this region is judged that the possibility of presence of the prehistoric sites is high.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.191-210
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• 2014

As mobile devices that can be connected to the Internet have spread and networking has become possible whenever/wherever, the Internet has become central in the dissemination and consumption of news. Accordingly, the ways news is gathered, disseminated, and consumed have changed greatly. In the traditional news media such as magazines and newspapers, expert editors determined what events were worthy of deploying their staffs or freelancers to cover and what stories from newswires or other sources would be printed. Furthermore, they determined how these stories would be displayed in their publications in terms of page placement, space allocation, type sizes, photographs, and other graphic elements. In turn, readers-news consumers-judged the importance of news not only by its subject and content, but also through subsidiary information such as its location and how it was displayed. Their judgments reflected their acceptance of an assumption that these expert editors had the knowledge and ability not only to serve as gatekeepers in determining what news was valuable and important but also how to rank its value and importance. As such, news assembled, dispensed, and consumed in this manner can be said to be expert-based recommended news. However, in the era of Internet news, the role of expert editors as gatekeepers has been greatly diminished. Many Internet news sites offer a huge volume of news on diverse topics from many media companies, thereby eliminating in many cases the gatekeeper role of expert editors. One result has been to turn news users from passive receptacles into activists who search for news that reflects their interests or tastes. To solve the problem of an overload of information and enhance the efficiency of news users' searches, Internet news sites have introduced numerous recommendation techniques. Recommendations based on popularity constitute one of the most frequently used of these techniques. This popularity-based approach shows a list of those news items that have been read and shared by many people, based on users' behavior such as clicks, evaluations, and sharing. "most-viewed list," "most-replied list," and "real-time issue" found on news sites belong to this system. Given that collective intelligence serves as the premise of these popularity-based recommendations, popularity-based news recommendations would be considered highly important because stories that have been read and shared by many people are presumably more likely to be better than those preferred by only a few people. However, these recommendations may reflect a popularity bias because stories judged likely to be more popular have been placed where they will be most noticeable. As a result, such stories are more likely to be continuously exposed and included in popularity-based recommended news lists. Popular news stories cannot be said to be necessarily those that are most important to readers. Given that many people use popularity-based recommended news and that the popularity-based recommendation approach greatly affects patterns of news use, a review of whether popularity-based news recommendations actually reflect important news can be said to be an indispensable procedure. Therefore, in this study, popularity-based news recommendations of an Internet news portal was compared with top placements of news in printed newspapers, and news users' judgments of which stories were personally and socially important were analyzed. The study was conducted in two stages. In the first stage, content analyses were used to compare the content of the popularity-based news recommendations of an Internet news site with those of the expert-based news recommendations of printed newspapers. Five days of news stories were collected. "most-viewed list" of the Naver portal site were used as the popularity-based recommendations; the expert-based recommendations were represented by the top pieces of news from five major daily newspapers-the Chosun Ilbo, the JoongAng Ilbo, the Dong-A Daily News, the Hankyoreh Shinmun, and the Kyunghyang Shinmun. In the second stage, along with the news stories collected in the first stage, some Internet news stories and some news stories from printed newspapers that the Internet and the newspapers did not have in common were randomly extracted and used in online questionnaire surveys that asked the importance of these selected news stories. According to our analysis, only 10.81% of the popularity-based news recommendations were similar in content with the expert-based news judgments. Therefore, the content of popularity-based news recommendations appears to be quite different from the content of expert-based recommendations. The differences in importance between these two groups of news stories were analyzed, and the results indicated that whereas the two groups did not differ significantly in their recommendations of stories of personal importance, the expert-based recommendations ranked higher in social importance. This study has importance for theory in its examination of popularity-based news recommendations from the two theoretical viewpoints of collective intelligence and popularity bias and by its use of both qualitative (content analysis) and quantitative methods (questionnaires). It also sheds light on the differences in the role of media channels that fulfill an agenda-setting function and Internet news sites that treat news from the viewpoint of markets.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.107-120
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• 2014

This study proposes a novel recommender system using the structural hole analysis to reflect qualitative and emotional information in recommendation process. Although collaborative filtering (CF) is known as the most popular recommendation algorithm, it has some limitations including scalability and sparsity problems. The scalability problem arises when the volume of users and items become quite large. It means that CF cannot scale up due to large computation time for finding neighbors from the user-item matrix as the number of users and items increases in real-world e-commerce sites. Sparsity is a common problem of most recommender systems due to the fact that users generally evaluate only a small portion of the whole items. In addition, the cold-start problem is the special case of the sparsity problem when users or items newly added to the system with no ratings at all. When the user's preference evaluation data is sparse, two users or items are unlikely to have common ratings, and finally, CF will predict ratings using a very limited number of similar users. Moreover, it may produces biased recommendations because similarity weights may be estimated using only a small portion of rating data. In this study, we suggest a novel limitation of the conventional CF. The limitation is that CF does not consider qualitative and emotional information about users in the recommendation process because it only utilizes user's preference scores of the user-item matrix. To address this novel limitation, this study proposes cluster-indexing CF model with the structural hole analysis for recommendations. In general, the structural hole means a location which connects two separate actors without any redundant connections in the network. The actor who occupies the structural hole can easily access to non-redundant, various and fresh information. Therefore, the actor who occupies the structural hole may be a important person in the focal network and he or she may be the representative person in the focal subgroup in the network. Thus, his or her characteristics may represent the general characteristics of the users in the focal subgroup. In this sense, we can distinguish friends and strangers of the focal user utilizing the structural hole analysis. This study uses the structural hole analysis to select structural holes in subgroups as an initial seeds for a cluster analysis. First, we gather data about users' preference ratings for items and their social network information. For gathering research data, we develop a data collection system. Then, we perform structural hole analysis and find structural holes of social network. Next, we use these structural holes as cluster centroids for the clustering algorithm. Finally, this study makes recommendations using CF within user's cluster, and compare the recommendation performances of comparative models. For implementing experiments of the proposed model, we composite the experimental results from two experiments. The first experiment is the structural hole analysis. For the first one, this study employs a software package for the analysis of social network data - UCINET version 6. The second one is for performing modified clustering, and CF using the result of the cluster analysis. We develop an experimental system using VBA (Visual Basic for Application) of Microsoft Excel 2007 for the second one. This study designs to analyzing clustering based on a novel similarity measure - Pearson correlation between user preference rating vectors for the modified clustering experiment. In addition, this study uses 'all-but-one' approach for the CF experiment. In order to validate the effectiveness of our proposed model, we apply three comparative types of CF models to the same dataset. The experimental results show that the proposed model outperforms the other comparative models. In especial, the proposed model significantly performs better than two comparative modes with the cluster analysis from the statistical significance test. However, the difference between the proposed model and the naive model does not have statistical significance.

• Journal of Distribution Science
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• v.9 no.4
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• pp.5-13
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• 2011

This study provides analysis of the effectiveness of domestic marketing strategies of the Korean coffee shop "Caffe Bene". It bases its evaluation on statistical outputs of 'choice attributes,' "market segmentation," demographic characteristics," and "satisfaction differences." The results are summarized in four points. First, five choice attributes were extracted from factor analysis: price, atmosphere, comfort, taste, and location; these are related to coffee shop selection behavior. Based on these five factors, cluster analysis was conducted, with statistical results classifying customers into three major groups: atmosphere oriented; comfort oriented; and taste oriented. Second, discriminant analysis tested cluster analysis and showed two discriminant functions: location and atmosphere. Third, cross-tabulation analysis based on demographic characteristics showed distinctive demographic characteristics within the three groups. Atmosphere oriented group, early-20s, as women of all ages was found to be 'walking down the street 'and 'through acquaintances' in many cases, as the cognitive path, and mostly found the store through 'outdoor advertising', and 'introduction'. Comfort oriented group was mainly women who are students in their early twenties or professionals, and appeared as a group to be very loyal because of high recommendation to other customers compared to other groups. Taste oriented group, unlike the other group, was mainly late-20s' college graduates, and was confirmed, as low loyalty, with lower recommendation activity. Fourth, to analyze satisfaction differences, one-way ANOVA was conducted. It shows that groups which show high satisfaction in the five main factors also show high menu satisfaction and high overall satisfaction. This results show that segmented marketing strategies are necessary because customers are considering price, atmosphere, comfort, taste, location when they choose coffee shop and demographics show different attributes based on segmented groups. For example, atmosphere oriented group is satisfied with shop interior and comfort while dissatisfied with price because most of the customers in this group are early 20s and do not have great financial capability. Thus, price discounting marketing strategies based on individual situations through CRM system is critical. Comfort oriented group shows high satisfaction level about location and shop comfort. Also, in this group, there are many early 20s female customers, students, and self-employed people. This group customers show high word of mouth tendency, hence providing positive brand image to the customers would be important. In case of taste oriented group, while the scores of taste and location are high, word of mouth score is low. This group is mainly composed of educated and professional many late 20s customers, therefore, menu differentiation, increasing quality of coffee taste and price discrimination is critical to increase customers' satisfaction. However, it is hard to generalize the results of study to other coffee shop brand, because this study have researched only one domestic coffee shop, Caffe Bene. Thus if future study expand the scope of locations, brands, and occupations, the results of the study would provide more generalizable results. Finally, research of customer satisfactions of menu, trust, loyalty, and switching cost would be critical in the future study.

• Quality Improvement in Health Care
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• v.4 no.1
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• pp.36-49
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• 1997

Background : Hypertension is one of the most important risk factors of the cerebrovascular accident and coronary artery disease which are the major causes of mortality in Korea. In Korea, the quality of care provided by office-based physicians has not been evaluated formally. The purpose of this study is to assess the quality of hypertension management of office-based physicians. Method : Self-administered questionnaires were mailed to the office-based physicians with the speciality of internal medicine, general surgery, family medicine, and general practitioners. Among 2,045 physicians, 981 doctors(48.0%) replied the questionnaires. Contents of questionnaires were based on the recommendation from the JNC-V report(the Fifth Report of the Joint National Committee on Detection, Evaluation, and Treatment of High Blood Pressure), and included the criteria of diagnosis, treatment, follow-up interval, and other characteristics of physicians(age, sex, type of speciality, and location of practice). Results : Eighty four percent of the office-based physicians made diagnosis of hypertension with less than 3 times of blood pressure measurements. The performance rate of required examination for hypertensives was very low in most items. Rate of fundoscopic examination is the lowest one among them(5.9%). The performance rate of laboratory examination was also low in most items. Internists tended to order more frequent laboratory examinations than any other type of physicians. Only 11.4% of the physicians did appropriate treatments for the mild hypertension case. The antihypertensives selected by the physicians as a first line drug were in the order of beta blocker(26.4%), calcium channel blocker(23.4%), diuretics(23.1%), ACE inhibitors(14.3%). The visit interval for established hypertensives was very short. Proportion of physicians with follow-up interval longer than 4 weeks was only 4.3%. Conclusions : The overall quality of hypertension management of office-based physicians in Korea is very problematic in many aspects. So further investigations to find out the reasons of low quality arid quality of care should be initiated.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.26 no.9
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• pp.821-827
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• 2015

Electromagnetic waves which are emitted from the Sun due to solar flare explosion can cause failures in HF radio communications in the day-side area of the Earth, that is so-call as Radio Blackouts. The international scale representing the severity of the Radio Blackouts is determined by the solar X-ray flux which is measured by United States Geostationary Operational Environmental Satellite. However, the scale is not always applicable to HF communication users in the different area on the Earth, because the HF communication effects depend not only on the X-ray strength but also on the subsolar point location. To solve this problem, we developed a HF radio spectrum monitoring system utilizing a spectrum analyzer. This system conducts a real-time measure of the HF spectrum, and automatically calculates signal to noise ratios and the occurrences of the HF blackouts as comparing with the interference level which is described from the ITU recommendation.