• Information and Communications Magazine
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• v.28 no.7
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• pp.59-68
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• 2011

스마트폰의 플랫폼화와 위치 측위 기술 및 관련 지도 DB의 개방은 위치 기반 서비스(LBS, Location Based Service)의 패러다임의 변화를 가져왔다. 위치 측위를 위한 HW의 제공, 위치 측위 API 및 프레임워크 제공, 지도 DB 및 각종 DB의 제공 등에 힘입어 LBS는 본격적인 성장을 맞이하고 있다. 또한 소셜 네트워크 서비스(SNS, Social Network Service), 증강 현실 (AR, Augmented Reality), 게임 등 다른 킬러앱과 연계하여 다양한 서비스를 제공하고 있으며 향후 안전 및 사고 예방 등의 공공적인 측면에서도 다양한 애플리케이션이 등장하고 있다. 그러나 이러한 급격한 패러다임의 변화는 개인정보 보호와 개인의 안전 및 편의성이라는 모순적인 이해관계 속에서 많은 문제점을 동시에 일으키고 있다. 본 고에서는 스마트폰이 가져온 LBS의 패러다임 변화 및 스마트폰 LBS의 기술, 서비스 방향을 정리하고 향후 과제 및 발전 방향에 대해서 살펴본다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.12
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• pp.2878-2884
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• 2015

Twitter, one of online social network services, is one of the most popular micro-blogs, which generates a large number of automated programs, known as tweet bots because of the open structure of Twitter. While these tweet bots are categorized to legitimate bots and malicious bots, it is important to detect tweet bots since malicious bots spread spam and malicious contents to human users. In the conventional work, temporal information was utilized for the classficiation of human and bot. In this paper, by utilizing geo-tagged tweets that provide high-precision location information of users, we first identify both Twitter users' exact location. Then, we propose a new tweet bot detection algorithm by using both an entropy based on geographic variable of each user and device information of each user. As a main result, the proposed algorithm shows superior bot detection and false alarm probabilities over the conventional result which only uses temporal information.

• International Journal of Computer Science & Network Security
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• v.21 no.8
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• pp.297-307
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• 2021

In the vibrant environment, documentation and managing systems are maintained autonomously through education foundations, book materials and libraries at the same time as information are not voluntarily accessible in a centralized location. At the moment Libraries are providing online resources and services for education activities. Moreover, libraries are applying outlets of social media such as Facebook as well as Instagrams to preview their services and procedures. Librarians with the assistance of promising tools and technology like analytics software are capable to accumulate more online information, analyse them for incorporating worth to their services. Thus Libraries can employ big data to construct enhanced decisions concerning collection developments, updating public spaces and tracking the purpose of library book materials. Big data is being produced due to library digitations and this has forced restrictions to academicians, researchers and policy creator's efforts in enhancing the quality and effectiveness. Accordingly, helping the library clients with research articles and book materials that are in line with the users interest is a big challenge and dispute based on Taibah university in Saudi Arabia. The issues of this domain brings the numerous sources of data from various institutions and sources into single place in real time which can be time consuming. The most important aim is to reduce the time that lapses among the authentic book reading and searching the specific study material.

• 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.

• Journal of Distribution Science
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• v.12 no.2
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• pp.95-103
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• 2014

Purpose - Korea has a better geographical location than other nations in the Northeast Asian region. This means that Korea has an opportunity to become the center of international physical distribution in Northeast Asia. Korea should take advantage of this opportunity by exploring appropriate strategies to achieve this goal, assuming government willingness, with a view to capitalizing on the geographical advantage of the Korean peninsula and constructing a comprehensive physical distribution network system. If we prepare for this scenario, Korea could become the center of international physical distribution in Northeast Asia. Research design, data, and methodology - This study has the purpose of determining how shipping companies form partnerships with third-party logistics providers, and the relevant implications. The survey methods used were personal interview and a questionnaire distributed through e-mail, fax, mail, and telephone. A total of 600 questionnaires were distributed, out of which 285 were returned. Of the collected questionnaires, 10 were excluded because of insufficient content, leaving 275 to be used in the study as available valid samples. The data that was collected from these samples was analyzed using the data coating process and by employing a statistical package program. Results - Flexible policies, administration, and systems will be needed to create better business practices. In this dissertation, first and foremost, the results reveal that in order to become the center of Northeast Asian logistics, Korea must transition into a new paradigm based on the current economic and social systems that have stemmed from bureaucracy, inflexibility, chauvinism, and egalitarianism. Flexible policies, administration, and systems will be required to create better business practices. Domestic logistics corporations need to occupy a strategic logistics hub, create a logistics network, and activate value-added logistics business strategies by ensuring significant manpower and by building a logistics information system to strengthen their competitive edge, creating an improved system. Conclusions - In this dissertation, first and foremost, we point out that in order to become a center of North East Logistics, Korea should change to a new paradigm from the old one based on current economic and social systems that have stemmed from bureaucracy, inflexibility, chauvinism, and egalitarianism. More reasonable business laws, systems, and policies based on market-driven flexibility and transparency should be created. Moreover, social norms and rules should be reasonably established, to accomplish political and social security. Korea has to cultivate a culture of tolerance for foreign companies. This involves a change of paradigm for the development of the capital city and satellite cities. It will take a powerful task force or organization to plan and execute the vision that aims to meet these needs, accomplish the necessary goals, use the appropriate system effectively, and make Korea a key country in the field of Northeast Asian logistics.

• Information Systems Review
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• v.20 no.2
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• pp.63-85
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• 2018

Emerging hotspot and trendy areas are formed into alleys and blocks with the help of viral effects among social network services (SNS) users called "Golmogleo." These users search for every corner of the alleys to share and promote their own favorite places through SNS. An analysis of hot places is limited if it is only based on macroeconomic indicators such as commercial area data published by national organizations, large-scale visiting facilities, and commuter figures. Careful analyses based on consumers' actual activities are needed. This study develops a "social big data analysis methodology" using Instagram data, which is one of the most popular SNSs suitable to identify recent consumer trends. We build a spatial analysis model using Local Moran's I. Results show that our model identifies new trend zones on the basis of posting data in Instagram, which are not included in the commercial information prepared by national organizations. The proposed analysis methodology enables better identification of the latest trend areas formulated by SNS user activities. It also provides practical information for start-ups, small business owners, and alley merchants for marketing purposes. This analytical methodology can be applied to future studies on social big data analysis.

• Journal of KIBIM
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• v.12 no.4
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• pp.104-115
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• 2022

Fine Dust in Korea has been classified as a social disaster since 2019 due to continuous increase in concentration of Particulate Matter 10(PM 10) and PM 2.5. The fine dust issue has negative physical and mental impacts, especially on vulnerable population including children and the elderly. Seoul metropolitan government have installed fine dust shelters since 2019. However, there is a lack of research that evaluates spatiotemporal distribution of these facilities. Therefore, the first aim of this study is to find the relationship between PM levels and dust scattering construction sites, or air pollutant emission sites through in depth spatial analyses. The second purpose is to analyze the spatial distribution of PM shelters in Seoul, and to evaluate the location efficiency of them. Kernel density, krigging, and network analyses were conducted, and floating population was considered instead of census data for this research. The reults of network analysis based on the road system showed that Yangcheon-gu, Songpa-gu, Seongbuk-gu, and Dobong-gu were found to need additional fine dust shelters. Also, the results from analyzing the floating population that includes children and the elderly showed that Songpa-gu, Seodaemun-gu, Gangdong-gu, Seocho-gu, and Dongdaemun-gu need more placements of find dust shelters. The results of this study are expected to provide implications for urban planners to enhance find dust shelter placement in urban areas, and vulnerable population issues would be considered in many ways.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.25-52
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• 2018

This study performs social network analysis based on consumer sentiment related to a location in Seoul using data reflecting consumers' web search activities and emotional evaluations associated with commerce. The study focuses on large commercial districts in Seoul. In addition, to consider their various aspects, social network indexes were combined with the trading area's public data to verify factors affecting the area's sales. According to R square's change, We can see that the model has a little high R square value even though it includes only the district's public data represented by static data. However, the present study confirmed that the R square of the model combined with the network index derived from the social network analysis was even improved much more. A regression analysis of the trading area's public data showed that the five factors of 'number of market district,' 'residential area per person,' 'satisfaction of residential environment,' 'rate of change of trade,' and 'survival rate over 3 years' among twenty two variables. The study confirmed a significant influence on the sales of the trading area. According to the results, 'residential area per person' has the highest standardized beta value. Therefore, 'residential area per person' has the strongest influence on commercial sales. In addition, 'residential area per person,' 'number of market district,' and 'survival rate over 3 years' were found to have positive effects on the sales of all trading area. Thus, as the number of market districts in the trading area increases, residential area per person increases, and as the survival rate over 3 years of each store in the trading area increases, sales increase. On the other hand, 'satisfaction of residential environment' and 'rate of change of trade' were found to have a negative effect on sales. In the case of 'satisfaction of residential environment,' sales increase when the satisfaction level is low. Therefore, as consumer dissatisfaction with the residential environment increases, sales increase. The 'rate of change of trade' shows that sales increase with the decreasing acceleration of transaction frequency. According to the social network analysis, of the 25 regional trading areas in Seoul, Yangcheon-gu has the highest degree of connection. In other words, it has common sentiments with many other trading areas. On the other hand, Nowon-gu and Jungrang-gu have the lowest degree of connection. In other words, they have relatively distinct sentiments from other trading areas. The social network indexes used in the combination model are 'density of ego network,' 'degree centrality,' 'closeness centrality,' 'betweenness centrality,' and 'eigenvector centrality.' The combined model analysis confirmed that the degree centrality and eigenvector centrality of the social network index have a significant influence on sales and the highest influence in the model. 'Degree centrality' has a negative effect on the sales of the districts. This implies that sales decrease when holding various sentiments of other trading area, which conflicts with general social myths. However, this result can be interpreted to mean that if a trading area has low 'degree centrality,' it delivers unique and special sentiments to consumers. The findings of this study can also be interpreted to mean that sales can be increased if the trading area increases consumer recognition by forming a unique sentiment and city atmosphere that distinguish it from other trading areas. On the other hand, 'eigenvector centrality' has the greatest effect on sales in the combined model. In addition, the results confirmed a positive effect on sales. This finding shows that sales increase when a trading area is connected to others with stronger centrality than when it has common sentiments with others. This study can be used as an empirical basis for establishing and implementing a city and trading area strategy plan considering consumers' desired sentiments. In addition, we expect to provide entrepreneurs and potential entrepreneurs entering the trading area with sentiments possessed by those in the trading area and directions into the trading area considering the district-sentiment structure.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.4
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• pp.31-37
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• 2017

Recently Drone technology is emerging as an alternative new way of distribution systems services. Amazon, Google which are global network chain distribution companies are developing an idea of Drone based delivery service and applied for patent for Drone distribution systems in USA. In this paper, we investigate a way to adopt Drone system to Air Cargo logistics, in particular, drone system based on combination of Light ID and RFID technology in the management procedure in stock warehouse. Also we explain the expected impact of Drone systems to customs declaration process. In this paper, we address the investigated limitations of Drone by the Korean Aviation Act as well as suggest the directions of future research for application of Drone to Air logistics industry with investigated limitations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.145-149
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• 2018

This paper introduces a method of sending and registering SMS using mobile LBS (Local Based Service) in social network service environment. This method acquires the location of the target person and object through the API and LBS, constructs the SMS based on the obtained information, and transmits and registers the SMS in the mobile environment. The composition of the SMS is the personal information of the object to be searched, the current position and the position of the object. Therefore, the user can quickly and accurately grasp the brief items and locations of objects to be searched through SMS. Also, Today we will improve the quality of life by providing upgraded service for shortening of appointment time and delivery.