• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.11
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• pp.2419-2425
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• 2011

Presently SmartPhone users over the 15 million are expected to exceed 20 million people by the end of the year. The prevalence of SmartPhone has brought positive results with a new paradigm. But, It makes a result that SmartPhone user should concentrate on mobile device and interpersonal relationships are avoided. In this paper, we design and implement user network services that use a same application using located information based on android.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.535-538
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• 2011

Presently SmartPhone users over the 15 million are expected to exceed 20 million people by the end of the year. The prevalence of SmartPhone has brought positive results with a new paradigm. But, It makes a result that SmartPhone user should concentrate on mobile device and interpersonal relationships are avoided. In this paper, we design and implement user network services that use a same application using located infomation based on android.

• The Journal of the Korea Contents Association
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• v.11 no.7
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• pp.60-69
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• 2011

As the mobile industry has developed, people have become to pursue more delicate information exchange and close relationships between individuals through it. According to such a request, Social Networking Services have been activated based on short messages. Moreover, in combination with smart phones, the needs for adding location information is recently increasing more and more. Security and Privacy problems, however, are raised because such location information is so sensitive and may be used maliciously by someone else. Especially, storing location information of family members in a public server may become a negative factor to hinder people from utilizing such services. Therefore, this paper proposes a location based SNS service using smart phones for home community that runs on a home server in a house so that relationships between family members at home may be closer and improved through utilizing the service.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.8
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• pp.1865-1872
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• 2013

The social network services are grown rapidly through dissemination of smart devices. Therefore, increasing the data exponentially because many people use web services. Using these big data, it will be needed study of providing customized knowledge. So in this paper, we had collected data of 40 people for implementation of knowledge service using big data during one month. Based on these data, we had inferred information of location and moving type, and evaluated accuracy. Through that we had studied personal experience knowledge evaluation model for knowledge service.

• Journal of Digital Convergence
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• v.11 no.3
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• pp.389-395
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• 2013

More sales of food and beverage coupons have been made using SNS on social commerce recently. If one buys coupons on social commerce, he/she can enjoy products at a lower price; however, there are drawbacks that one must consider such as location, service hours, and discount rate. Thus, this paper suggests a system that recommends food and beverage coupons on social commerce for users that considers a user's personal context of location, time, and purchase history. In order to reflect a user's context awareness and continuous preference, this paper suggests a method based on the Bayesian network. In order to reflect personalized weighting on the standard of coupon selection to match a user's preference, a measurement and classification of weighting preferences is performed on the basis of AHP. 20 experiments in one month involving 12 students were carried out to verify the effectiveness of the system, resulting in an 80% satisfaction level.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.377-379
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• 2022

POI refers to the point of Interest in Location-Based Social Networks (LBSNs). With the rapid development of mobile devices, GPS, and the Web (web2.0 and 3.0), LBSNs have attracted many users to share their information, physical location (real-time location), and interesting places. The tremendous demand of the user in LBSNs leads the recommendation systems (RSs) to become more widespread attention. Recommendation systems assist users in discovering interesting local attractions or facilities and help social network service (SNS) providers based on user locations. Therefore, it plays a vital role in LBSNs, namely POI recommendation system. In the machine learning model, most of the training data are stored in the centralized data storage, so information that belongs to the user will store in the centralized storage, and users may face privacy issues. Moreover, sharing the information may have safety concerns because of uploading or sharing their real-time location with others through social network media. According to the privacy concern issue, the paper proposes a recommendation model to prevent user privacy and eliminate traditional RS problems such as cold-start and data sparsity.

• Journal of Internet Computing and Services
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• v.12 no.1
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• pp.99-110
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• 2011

Mobile environments rapidly changing and digital convergence widely employed, mobile devices including smart phones have been playing a critical role that changes users' lifestyle in the areas of entertainments, businesses and information services. The various services using mobile devices are developing to meet the personal needs of users in the mobile environments. Especially, an LBS (Location-Based Service) is combined with other services and contents such as augmented reality, mobile SNS (Social Network Service), games, and searching, which can provide convenient and useful services to mobile users. In this paper, we design and implement the prototype of mobile personal assistant (PA) agents. Our personal assistant agent helps users do some tasks by hiding the complexity of difficult tasks, performing tasks on behalf of the users, and reflecting the preferences of users. To identify user's preferences and provide personalized services, clustering and classification algorithms of data mining are applied. The clusters of the log data using clustering algorithms are made by measuring the dissimilarity between two objects based on usage patterns. The classification algorithms produce user profiles within each cluster, which make it possible for PA agents to provide users with personalized services and contents. In the experiment, we measured the classification accuracy of user model clustered using clustering algorithms. It turned out that the classification accuracy using our method was increased by 17.42%, compared with that using other clustering algorithms.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.3
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• pp.303-309
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• 2011

Situation awareness services which increasingly expand their influence in everyday life can be classified into location-based service and social network service. Their quality of service (QoS) can be differed based on the location accuracy of smart phones and accuracy of directional recognition technology. This study was conducted to analyze GPS, digital compass, radio communication, and geospatial web information which can provide a clue in using the situation aware services based on lab experiments and surveys. According to the result of lab experiment on accuracy of determining location / direction with smart phones, owing to inherent lack of indoor accuracy in determining position and direction, as well as errors in spatial data used as platform, it was found that devices were not provided with sufficiently accurate data when using the situation aware services indoors compared to outdoors. To enhance accuracy of determining indoor positions, there are several methods including location metering based on Wi-Fi, which had several problems compared with GPS used in outdoor environment. Thus, it was determined that more study would be necessary to solve these issues.

• Smart Media Journal
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• v.3 no.1
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• pp.9-15
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• 2014

In these days, along with the extreme popularity of online social network services, it becomes an important problem understanding the role of social network in the research of message dissemination. Past studies of message dissemination over online social network services mostly consider the coverage of message dissemination and the methods to maximize it. But, these works lack of the consideration of the impact of multi channel social network, which has multiple communication channel with distinct properties of message transfer and various users with distinct channel preferences. In this paper, the new message dissemination model over multi-modal multi-channel social network, the Delay Weighted Independent Cascade Model, is proposed. The proposed model considers various channels including online social network service, email, SMS messaging, phone and mouth-to-mouth and their distinct message transfer properties. In order to consider the various user properties, the different value of probability of forwarding a message and the different preference of communication channel is considered. Moreover, the proposed model considers the distribution of user location and allows to analyze the properties of message dissemination under various scenarios. Based on the proposed model, a message dissemination simulator is generated and the message disseminations on various scenarios are analyzed.

• Journal of Cadastre & Land InformatiX
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• v.48 no.2
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• pp.109-119
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• 2018

Point of interest (POI) of the city is a special place that has what importance to the user. For example, it is such landmark, restaurants, museums, hotels, and theaters. Because of its role in the social and economic life of us, these have attracted a lot of interest in location-based applications such as social networks and online map. However, while it can easily be obtained through the Web, the basic information of POI such as geographic location, another effort is required to obtain detailed information such as Wi-Fi, accepting credit cards, opening hours, romper room and the assessment and evaluation of other users. To solve these problems, a new method for correcting position error is required to link location-based social network service (LBSNS) data and POIs. This paper attempts to propose a position error correction method of POI and LBSNS data to enrich POI information from the vast information that is accumulated in LBSNS. Through this study, we can overcome the limitation of individual POI information via the information fusion method of LBSNS and POI, and we have discovered the possibility to be able to provide additional information which users need. As a result, we expect to be able to collect a variety of POI information quickly.