• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.2
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• pp.195-203
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• 2018

With the explosion of SNS(social network services) users, the social commerce market has emerged as a new consumer market, and will continue to grow in recent years. Despite the market environment, however, studies are lacking as to the causes of frustration that are hurting social commerce activation. This study is based on the 'Hezbollah' 2 Factor Theory and is a study of social commerce users' satisfaction and frustration factors. For this purpose, social commerce site characteristics and user characteristics were first derived from interviews and literature reviews to confirm their relationship to satisfaction and dissatisfied products. The results showed that the price discount rate, diversity, regional infrastructure, and e-commerce familiarity resulted in the impact on the definition of satisfaction, while the price discount rate, interoperability and innovation resulted in the definition of unsatisfactory goods. It also showed that satisfaction affects the definition of intended use. In particular, the price discount rate was found to be the only factor affecting the definition of unsatisfactory as well as affecting the definition of satisfaction.

• Journal of KIISE
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• v.42 no.5
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• pp.637-641
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• 2015

Due to the recent increasement of user created contents like SNS, blog posts, and so on, broadcast contents are actively re-construction by its users. Especially, on some genres like drama, movie, various information from cars and film sites to clothes and watches in a content is spreaded out to other users through blog postings. Since such information can be an additional information for the content, they can be used for providing high-quality broadcast services. For this purpose, in this paper, we propose timeline tag cloud generation method for broadcasting contents. In the proposed method, blog postings on the target contents are first gathered and then, images and words around images are extracted from a blog post as a tag set. An extracted tag set is tagged on a specific timeline of the target content. In experiments, to prove the efficiency of the proposed method, we evaluated the performances of the proposed image matching and tag cloud generation methods.

• The KIPS Transactions:PartC
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• v.19C no.1
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• pp.29-38
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• 2012

Due to rapid spread of smart phones and SNS(Social Network Service), using of Internet applications has increased and taking up bandwidth more than 3G network's capacity recently. This caused reduction of speed and service quality, and occurred strong needs that backbone network company to increasing investment costs. Also a great rise of mobile network users causing identity management problems on mobile service provider through mobile network. This paper proposes advanced IDM3G[1] - to solve user ID management and security problems on mobile internet application services over 3G network and more - authentication management protocol. $I^2DM$ protocol breakup loads which made by existing IDM3G protocol's mutual authentication via mobile operator, via sending some parts to internet application service provider, enhancing mobile and ID management of service provider and network load and process load from information handling and numbers of transmitting packets, to suggest more optimized protocol against further demanding of 3G mobile network.

• The Journal of the Korea Contents Association
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• v.19 no.2
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• pp.1-10
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• 2019

The present research aims to identify the issues that occurred when uploading stock photos to the internet-based stock image agencies and to develop technical solutions based on web service technologies. We identify the issues by examination of previous studies and stock photo uploading systems of major three agencies currently in service. As such, we develop web service technology by focusing on the following matters. First, we apply an automatic tag system to ensure convenience. Second, to ensure safety, we apply a technology that easily enables prevention of portrait rights violations and trademark infringements. We also prepare for measures against possible harmfulness. Third, to ensure completeness, we apply a method which resolves upload failure issues that frequently occurred in the past. In particular, the present research is significant as it applies an automatic image analysis system based on Google Cloud Vision API as the artificial intelligence-based image processing technology. In addition, we develop a web service program which improves user access by using SNS-type screen composition.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.21 no.1
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• pp.53-63
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• 2011

An SNS(Social Network Service) enables people to form a social network on online as in the real world. With the rising popularity of the service, side effects of SNSs were issued. Therefore we propose and implement a policy-based privacy protection module and access control policy language for ensuring the right of control of personal information and sharing data among SNSs. The policy language for protecting privacy is based on an attribute-based access control model which grants an access to personal information based on a user's attributes. The policy language and the privacy protection module proposed to give the right of control of personal information to the owner, they can be adopted to other application domains in which privacy protection is needed as well as secure sharing data among SNSs.

• Journal of the Korea Society of Computer and Information
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• v.26 no.1
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• pp.163-170
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• 2021

As a big data is being used in various industries, big data market is expanding from hardware to infrastructure software to service software. Especially it is expanding into a huge platform market that provides applications for holistic and intuitive visualizations such as big data meaning interpretation understandability, and analysis results. Demand for big data extraction and analysis using social media such as SNS is very active not only for companies but also for individuals. However despite such high demand for the collection and analysis of social media data for user trend analysis and marketing, there is a lack of research to address the difficulty of dynamic interlocking and the complexity of building and operating software platforms due to the heterogeneity of various social media service interfaces. In this paper, we propose a method for developing a framework to operate the process from collection to extraction and classification of social media data. The proposed framework solves the problem of heterogeneous social media data collection channels through adapter patterns, and improves the accuracy of social topic extraction and classification through semantic association-based extraction techniques and topic association-based classification techniques.

• KIISE Transactions on Computing Practices
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• v.21 no.2
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• pp.154-159
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• 2015

Over the past few years, user needs in the smartphone application market have been shifted from diversity toward intelligence. Here, we propose a novel cognitive agent that plans the daily routines of users using the lifelog data collected by the smart phones of individuals. The proposed method first employs DPGMM (Dirichlet Process Gaussian Mixture Model) to automatically extract the users' POI (Point of Interest) from the lifelog data. After extraction, the POI and other meaningful features such as GPS, the user's activity label extracted from the log data is then used to learn the patterns of the user's daily routine by POMDP (Partially Observable Markov Decision Process). To determine the significant patterns within the user's time dependent patterns, collaboration was made with the SNS application Foursquare to record the locations visited by the user and the activities that the user had performed. The method was evaluated by predicting the daily routine of seven users with 3300 feedback data. Experimental results showed that daily routine scheduling can be established after seven days of lifelogged data and feedback data have been collected, demonstrating the potential of the new method of place-time-activity coupled daily routine planning systems in the intelligence application market.

• The Journal of the Korea Contents Association
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• v.17 no.11
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• pp.60-69
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• 2017

Recently, with the rapid development of internet and smart phones, social network services that can create and share various information through relationships among users have been actively used. Especially as the amount of information becomes enormous and unreliable information increases, expert recommendation that can offer necessary information to users have been studied. In this paper, we propose an expert recommendation scheme considering users' interests, human relations, and response quality. The users' interests are evaluated by analyzing their past activities in social network. The human relations are evaluated by extracting the users who have the same interesting fields. The response quality is evaluated by considering the user's response speed and response contents. The proposed scheme determines the user's expert score by combining the users' interests, the human relations, and the response quality. Finally, we recommend proper experts by matching queries and expert groups. It is shown through various performance evaluations that the proposed scheme outperforms the existing schemes.

• The Journal of the Korea Contents Association
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• v.16 no.4
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• pp.434-441
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• 2016

Using bigdata analysis procedures, the present study sought to review and explore the various aspects of self-disclosure and boundary impermeability of worldwide twitter users. A total of 415 million tweets issued by 54 million users were collected during 6 months and the users of top 10 languages were investigated. And the effect of languages of twitter users on the boundary impermeability, disclosure rate of user profile, profile image, geographical information, URL in profile and user description were analyzed in this study. The results showed that the boundary impermeability and all the self-disclosure rates of twitter users (profile, profile image, geographical information, URL in profile, user description) were significantly (p<0.001) different among language groups of users. The self-disclosure rates and the average points of Portuguese, Indonesian and Spanish users were higher than those of Arabic, Japanese, Turkish and Korean users. The results also showed a positive relationship between boundary impermeability and the number of tweets (including retweets) issued by each users.

• Journal of Digital Convergence
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• v.15 no.1
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• pp.427-433
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• 2017

Mobile game users tend to value the opinions from their friends or SNS when making a decision on which game to play. This is because they are not satisfied with the information on suggestions provided by the conventional mobile game recommendation systems. In this research, we made a system that can reflect user preference directly by using Analytic Hierarchy Process(AHP). In the system, the hierarchy of AHP is composed of final goal(Level 1), evaluation basis(Level 2) and alternative(Level 3). And the system is made up of an input module, an AHP processing module, a recommendation module and database. Through comparison analysis with two conventional systems to test the performance of the system, we could find that the system got more higher satisfaction than the other systems.