• Journal of the Korea Society of Computer and Information
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• v.20 no.11
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• pp.143-150
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• 2015

Social network services can be defined as an individual web page which enables online, human-relationship building by collecting useful information and sharing it with specific or unspecific people. Recently, as the social network services(SNS) such as Twitter and Facebook have been paid attention in many fields of the society. SNSs are also one of the fastest channels to get news which people may not be able to see on TV or newspaper. The number of people who feel they are benefiting from social network services are increasing dramatically. A number of researches about SNS are underway. The study based on the Technology Acceptance Model empirically investigates the relationship between characteristics of SNS (system, service, information, and emotional) and user satisfaction of SNS. The study also analyzes how the relationshipa between SNS characteristics, satisfaction and user acceptance are moderated by country type of SNS users and inclination toward SNS acceptance. To achieve these research purposes, the study conducted various statistical analyses using questionnaire of the Korean and Chinese SNS users. The results of the study are followings. First, SNS characteristics have a positive effect to the user satisfaction. Second, SNS satisfaction have a positive effect to the user acceptance. Third, the relationship between SNS characteristics and user satisfaction is moderated by the country type of SNS users and inclination toward SNS acceptance. The study results could provide some implications to researchers who have interest in studying SNS, also could help business managers to operate and develop their SNS site more effectively.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.25-44
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• 2013

Accessing movie contents has become easier and increased with the advent of smart TV, IPTV and web services that are able to be used to search and watch movies. In this situation, there are increasing search for preference movie contents of users. However, since the amount of provided movie contents is too large, the user needs more effort and time for searching the movie contents. Hence, there are a lot of researches for recommendations of personalized item through analysis and clustering of the user preferences and user profiles. In this study, we propose recommendation system which uses ontology based knowledge base. Our ontology can represent not only relations between metadata of movies but also relations between metadata and profile of user. The relation of each metadata can show similarity between movies. In order to build, the knowledge base our ontology model is considered two aspects which are the movie metadata model and the user model. On the part of build the movie metadata model based on ontology, we decide main metadata that are genre, actor/actress, keywords and synopsis. Those affect that users choose the interested movie. And there are demographic information of user and relation between user and movie metadata in user model. In our model, movie ontology model consists of seven concepts (Movie, Genre, Keywords, Synopsis Keywords, Character, and Person), eight attributes (title, rating, limit, description, character name, character description, person job, person name) and ten relations between concepts. For our knowledge base, we input individual data of 14,374 movies for each concept in contents ontology model. This movie metadata knowledge base is used to search the movie that is related to interesting metadata of user. And it can search the similar movie through relations between concepts. We also propose the architecture for movie recommendation. The proposed architecture consists of four components. The first component search candidate movies based the demographic information of the user. In this component, we decide the group of users according to demographic information to recommend the movie for each group and define the rule to decide the group of users. We generate the query that be used to search the candidate movie for recommendation in this component. The second component search candidate movies based user preference. When users choose the movie, users consider metadata such as genre, actor/actress, synopsis, keywords. Users input their preference and then in this component, system search the movie based on users preferences. The proposed system can search the similar movie through relation between concepts, unlike existing movie recommendation systems. Each metadata of recommended candidate movies have weight that will be used for deciding recommendation order. The third component the merges results of first component and second component. In this step, we calculate the weight of movies using the weight value of metadata for each movie. Then we sort movies order by the weight value. The fourth component analyzes result of third component, and then it decides level of the contribution of metadata. And we apply contribution weight to metadata. Finally, we use the result of this step as recommendation for users. We test the usability of the proposed scheme by using web application. We implement that web application for experimental process by using JSP, Java Script and prot$\acute{e}$g$\acute{e}$ API. In our experiment, we collect results of 20 men and woman, ranging in age from 20 to 29. And we use 7,418 movies with rating that is not fewer than 7.0. In order to experiment, we provide Top-5, Top-10 and Top-20 recommended movies to user, and then users choose interested movies. The result of experiment is that average number of to choose interested movie are 2.1 in Top-5, 3.35 in Top-10, 6.35 in Top-20. It is better than results that are yielded by for each metadata.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.1
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• pp.76-81
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• 2018

The Internet of Things (IoT), which is emerging as a future economic growth engine, has been actively introduced in areas close to our daily lives. However, there are still IoT security threats that need to be resolved. In particular, with the spread of smart homes and smart cities, an explosive amount of closed-circuit televisions (CCTVs) have been installed. The Internet protocol (IP) information and even port numbers assigned to CCTVs are open to the public via search engines of web portals or on social media platforms, such as Facebook and Twitter; even with simple tools these pieces of information can be easily hacked. For this reason, a big-data analytics system is needed, capable of supporting quick responses against data, that can potentially contain risk factors to security or illegal websites that may cause social problems, by assisting in analyzing data collected by search engines and social media platforms, frequently utilized by Internet users, as well as data on illegal websites.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.6 no.2
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• pp.26-33
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• 2007

Social cost has been increased by traffic accident and congestion since early 1990s. The construction of roadways and railways has been suggested as countermeasures. However, ITS has finally introduced as a logical solution because the expenses of infrastructures are costly. The data collection field has developed through numerous researches and pilot projects. However the information provision field does need a lot of study. The traffic information broadcasting whether simple traffic information or the value-added information has been available via radio, television and internet which does not require tremendous investment compared with data collection stage. Therefore, this study reviews the suitability of the gadget service usually offered by window vista users which is the result of the development of technology and the changes of internet environment. It also suggests to using the RSS(Really Simple Syndication) manner as a basic method to provide the traffic information based on the needs of user in order to enhance the usability of traffic information. For this, this study analyzes the current methods and techniques of traffic information service which is widely available by local governments and companies and suggest possible changes and methods in order to provide Gadget-based service to the public.