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The Journal of Society for e-Business Studies
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Society for e-Business Studies
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Volume & Issues
Volume 21, Issue 3 - Aug 2016
Volume 21, Issue 2 - May 2016
Volume 21, Issue 1 - Feb 2016
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A Method for Calculating Exposure Risks of Privacy Information based on Website Structures
Lee, Sue Kyoung ; Son, Jin Sik ; Kim, Kwanho ;
The Journal of Society for e-Business Studies, volume 21, issue 1, 2016, Pages 1~14
DOI : 10.7838/jsebs.2016.21.1.001
This research proposes a method that aims to evaluate the risk levels of websites based on exposure risks of privacy information. The proposed method considers two aspects as follows. First, we define the risk levels of each privacy information according to its own inherent risk. Second, we calculate the visiting probability of a webpage to measure the expected of the actual exposure of privacy information on that webpage. In this research, we implemented an system to prove that automatically collects websites and calculates their risk levels. For the experiments, we used a real world dataset consisting of a total of websites for 4 categories such as university, bank, central government agency, and education. The experiment results show that the websites in the bank category are relatively well managed, while the others are needed to cope with the exposure of privacy information. Finally, the proposed method in this research is expected to be further utilized in establishing a priority-based approach to alleviate of the privacy information exposure problems.
A Morphological Analysis Method of Predicting Place-Event Performance by Online News Titles
Choi, Sukjae ; Lee, Jaewoong ; Kwon, Ohbyung ;
The Journal of Society for e-Business Studies, volume 21, issue 1, 2016, Pages 15~32
DOI : 10.7838/jsebs.2016.21.1.015
Online news on the Internet, as published open data, contain facts or opinions about a specific affair and hence influences considerably on the decisions of the general publics who are interested in a particular issue. Therefore, we can predict the people`s choices related with the issue by analyzing a large number of related internet news. This study aims to propose a text analysis methodto predict the outcomes of events that take place in a specific place. We used topics of the news articles because the topics contains more essential text than the news articles. Moreover, when it comes to mobile environment, people tend to rely more on the news topics before clicking into the news articles. We collected the titles of news articles and divided them into the learning and evaluation data set. Morphemes are extracted and their polarity values are identified with the learning data. Then we analyzed the sensitivity of the entire articles. As a result, the prediction success rate was 70.6% and it showed a clear difference with other analytical methods to compare. Derived prediction information will be helpful in determining the expected demand of goods when preparing the event.
The Impact of Functional and Emotional Factors on User Satisfaction and Commitment toward Mobile Messenger Service: Investigating the Mediating Effects of Intimacy and Fatigue
Lee, Ae Ri ; Park, Yong Wan ; Park, Yujin ;
The Journal of Society for e-Business Studies, volume 21, issue 1, 2016, Pages 33~63
DOI : 10.7838/jsebs.2016.21.1.033
The diffusion of smartphone has make people engaged in communication with mobile messenger in everyday life. To understand the rapid growth of mobile messenger usage, this study investigates the unique features of mobile messenger services as communication media. Based on the media synchronicity theory and literature about online communication, we identify the functional and emotional features of mobile messenger. In particular, this study demonstrates that functional and emotional features of mobile messenger would influence intimacy and fatigue. Also, intimacy and fatigue, as mediating variables, have an impact on user satisfaction and commitment toward mobile messenger service. The results of this study provide practical implications for mobile messenger providers and users which attempt to facilitate positive effect such as intimacy among users and reduce negative effect such as fatigue on mobile messenger communication.
A Two-Phase On-Device Analysis for Gender Prediction of Mobile Users Using Discriminative and Popular Wordsets
Choi, Yerim ; Park, Kyuyon ; Kim, Solee ; Park, Jonghun ;
The Journal of Society for e-Business Studies, volume 21, issue 1, 2016, Pages 65~77
DOI : 10.7838/jsebs.2016.21.1.065
As respecting one`s privacy becomes an important issue in mobile device data analysis, on-device analysis is getting attention, in which the data analysis is conducted inside a mobile device without sending data from the device to outside. One possible application of the on-device analysis is gender prediction using text data in mobile devices, such as text messages, search keyword, website bookmarks, and contact, which are highly private, and the limited computing power of mobile devices can be addressed by utilizing the word comparison method, where words are selected beforehand and delivered to a mobile device of a user to determine the user`s gender by matching mobile text data and the selected words. Moreover, it is known that performing prediction after filtering instances using definite evidences increases accuracy and reduces computational complexity. In this regard, we propose a two-phase approach to on-device gender prediction, where both discriminability and popularity of a word are sequentially considered. The proposed method performs predictions using a few highly discriminative words for all instances and popular words for unclassified instances from the previous prediction. From the experiments conducted on real-world dataset, the proposed method outperformed the compared methods.
Application Suite for Autonomous Management and Service of Verbal Knowledge
Yoo, Keedong ;
The Journal of Society for e-Business Studies, volume 21, issue 1, 2016, Pages 79~90
DOI : 10.7838/jsebs.2016.21.1.079
Autonomous knowledge service, a fully-automated and pervasive service for knowledge acquisition and support based on the power of recent ITs is gaining tremendous interest more and more, as not only the level of users` intelligence increases but also the maturity of IT infrastructure improves. Conventional approaches of knowledge service, however, could not satisfy users because they usually provided undesired knowledge which had been acquired without considering users` want. In other words, knowledge acquisition and distribution were separately performed. This research, therefore, suggests an amended autonomous knowledge service framework by fully-automating the whole phases of knowledge life cycle, from knowledge acquisition to distribution. ASKs, the prototype system of this research, is also implemented by defining and specifying component technologies which constituently compose suggested framework. More user-friendly and applicable way of knowledge service will be derived and facilitated through this research.
A Literature Review on Information Visualization of Manufacturing Industry Sector
Chang, Tai-Woo ;
The Journal of Society for e-Business Studies, volume 21, issue 1, 2016, Pages 91~104
DOI : 10.7838/jsebs.2016.21.1.091
Business intelligence based on the data analysis come into the spotlight. Especially, information visualization of the analysis result is treated significantly. given the interest in big data technologies. Because corporate managers want to use the results of data analysis in the decision-making process and the visualization technology will give help with cognitive function and operation function. In this paper, the status of information visualization is reviewed and analyzed from the viewpoint of manufacturing service. Several implications are drawn and it is expected that they will help to developers and administrators of manufacturing sector who want to adopt information visualization applications.
A Study on Improved Detection Signature System in Hacking Response of One-Line Games
Lee, Chang Seon ; Yoo, Jinho ;
The Journal of Society for e-Business Studies, volume 21, issue 1, 2016, Pages 105~118
DOI : 10.7838/jsebs.2016.21.1.105
Game companies are frequently attacked by attackers while the companies are servicing their own games. This paper analyzes the limit of the Signature detection method, which is a way of detecting hacking modules in online games, and then this paper proposes the Scoring Signature detection scheme to make up for these problems derived from the limits. The Scoring Signature detection scheme enabled us to detect unknown hacking attacks, and this new scheme turned out to have more than twenty times of success than the existing signature detection methods. If we apply this Scoring Signature detection scheme and the existing detection methods at the same time, it seems to minimize the inconvenient situations to collect hacking modules. And also it is expected to greatly reduce the amount of using hacking modules in games which had not been detected yet.
Research of Topic Analysis for Extracting the Relationship between Science Data
Kim, Mucheol ;
The Journal of Society for e-Business Studies, volume 21, issue 1, 2016, Pages 119~129
DOI : 10.7838/jsebs.2016.21.1.119
With the development of web, amount of information are generated in social web. Then many researchers are focused on the extracting and analyzing social issues from various social data. The proposed approach performed gathering the science data and analyzing with LDA algorithm. It generated the clusters which represent the social topics related to `health`. As a result, we could deduce the relationship between science data and social issues.
An Empirical Research on Information Privacy Risks and Policy Model in the Big data Era
Park, Cheon Woong ; Kim, Jun Woo ; Kwon, Hyuk Jun ;
The Journal of Society for e-Business Studies, volume 21, issue 1, 2016, Pages 131~145
DOI : 10.7838/jsebs.2016.21.1.131
A Study on Method for User Gender Prediction Using Multi-Modal Smart Device Log Data
Kim, Yoonjung ; Choi, Yerim ; Kim, Solee ; Park, Kyuyon ; Park, Jonghun ;
The Journal of Society for e-Business Studies, volume 21, issue 1, 2016, Pages 147~163
DOI : 10.7838/jsebs.2016.21.1.147
Gender information of a smart device user is essential to provide personalized services, and multi-modal data obtained from the device is useful for predicting the gender of the user. However, the method for utilizing each of the multi-modal data for gender prediction differs according to the characteristics of the data. Therefore, in this study, an ensemble method for predicting the gender of a smart device user by using three classifiers that have text, application, and acceleration data as inputs, respectively, is proposed. To alleviate privacy issues that occur when text data generated in a smart device are sent outside, a classification method which scans smart device text data only on the device and classifies the gender of the user by matching text data with predefined sets of word. An application based classifier assigns gender labels to executed applications and predicts gender of the user by comparing the label ratio. Acceleration data is used with Support Vector Machine to classify user gender. The proposed method was evaluated by using the actual smart device log data collected from an Android application. The experimental results showed that the proposed method outperformed the compared methods.