• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.3
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• pp.525-532
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• 2013

Recently. smartphones have been popularized rapidly and now located deep in our daily life, providing a variety of services from banking, SNS (Social Network Service), and entertainment to smart-work mobile office through apps. Such smartphone apps can be easily downloaded from what is known as app store which, however, bears many security issues as software developers can just as easily upload to it. Military apps will be exposed to a myriad of security threats if distributed through internet-basis commercial app store. In order to mitigate such security concerns, this paper suggests a security guidelines for establishing a military-excusive app store and security verification system which prevent the security hazards that can occur during the process of development and distribution of military-use mobile apps.

• 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.

• Spatial Information Research
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• v.22 no.3
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• pp.1-8
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• 2014

While SNS services such as Twitter or Facebook are rapidly growing, research for the SNS analysis has been concerned. Especially, twitter reacts to social issues in real-time so that it is used to get useful experimental data for researchers of social science or information retrieval. However, it is still lack of research on the methodology to collect data. Therefore, this paper suggests the tweet acquisition system by considering tendency of twitter user oriented location-based event and political social event. First the system acquires tweets including information of location and keyword about event and secure IDs for acquisition of political social event. Then we plan ID-analyzer to classify the tendency of users. In addition for measuring reliability of ID-analyzer, it acquires and analyzes the tweet by using high-ranked ID. In analyses result, top-ranked ID shows 88.8% reliability, 2nd-ranked ID shows 76.05% and ID-analyzer shows 77.5%, it shortens collection time by using minority ID.

• The Journal of Bigdata
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• v.1 no.1
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• pp.61-66
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• 2016

With big data analysis, companies use the customized marketing strategy based on customer's information. However, because of the concerns about privacy issue and identity theft, people start erasing their personal information or changing the privacy settings on social network site. Facebook, the most used social networking site, has the feature called 'Likes' which can be used as a tool to predict user's demographic profiles, such as sex and age range. To make accurate analysis model for the study, 'Likes' data has been processed by using Gaussian RBF and nFactors for dimensionality reduction. With random Forest and 5-fold cross-validation, the result shows that sex has 75% and age has 97.85% accuracy rate. From this study, we expect to provide an useful guideline for companies and marketers who are suffering to collect customers' data.

• The Journal of Bigdata
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• v.5 no.1
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• pp.197-208
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• 2020

Lexical ambiguity means that a word can be interpreted as two or more meanings, such as homonym and polysemy, and there are many cases of word sense ambiguation in words expressing emotions. In terms of projecting human psychology, these words convey specific and rich contexts, resulting in lexical ambiguity. In this study, we propose an emotional classification model that disambiguate word sense using bidirectional LSTM. It is based on the assumption that if the information of the surrounding context is fully reflected, the problem of lexical ambiguity can be solved and the emotions that the sentence wants to express can be expressed as one. Bidirectional LSTM is an algorithm that is frequently used in the field of natural language processing research requiring contextual information and is also intended to be used in this study to learn context. GloVe embedding is used as the embedding layer of this research model, and the performance of this model was verified compared to the model applied with LSTM and RNN algorithms. Such a framework could contribute to various fields, including marketing, which could connect the emotions of SNS users to their desire for consumption.

• Journal of Digital Convergence
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• v.15 no.2
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• pp.309-318
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• 2017

This study is for analyzing the tone, the frame and the characteristics of political news in social media. Social news media is not same as old media in sharing news freely by SNS like tweeter, facebook and reporting, editing by anyone using SNS with various opinions. With Content analysis, sampling 419 cases from 'Wikitree' by the keyword, 'presidential election', all the full text analysed each how is social media making public opinion differently and which frame is using in. As the result, the social media has different tone, frame, and characteristic due to the reported figure, type of report, information source, attitude to the government, specifically shows a lack of in-depth report and distinct soft-journalism just same as old media's. Because the tone of social news media is not probable, specific but improbable, vague, using the irrational, strategic and episodic frame mainly.

• The Journal of the Korea institute of electronic communication sciences
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• v.9 no.11
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• pp.1323-1330
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• 2014

As for civil service support, the interaction between citizens as well as the government and citizens has an important value, and the participation between citizens be very important. The interaction between these citizens can lead to spreading the use of the app by getting them to share their status information with an specified number of people in the public service such as a social network service. Mobile-based social network service has various built-in sensors to increase the interaction between the government and citizens and post the status information of users on SNS. In this regard, this paper proposed a social network application for civil services based on the Android by using location-based context information. Experimental results showed that since the application proposed in this paper can be applied to low-performance system and exhibits high performance, it can allow users located at a short distance to detect new information and share contents by adding the content to SNS which is the closest to the location of users.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.10
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• pp.1309-1316
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• 2016

This paper suggests adjusting TCP for smartphones that often have small size data transmission tendency. Usage of smartphones has been risen dramatically in recent years, including frequent usage of real-time map search, public transportation search, online games, and SNS. Because the small size data transmission ends before the phase of the TCP congestion avoidance, this paper suggests an algorithm that increases the transmission speed ahead of the traffic congestion event. The algorithm reduces unnecessary delay by data size-driven adjustment of the Linux Quick ACK and Nagle's algorithm. Therefore, TCP is improved to maintain a high transmission rate steadily in small data transmission.

• Journal of the Korean Society of Radiology
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• v.13 no.6
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• pp.865-872
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• 2019

The purpose of this study was to analyze the correlation between radiation information sources and major selection satisfaction in radiologic science students of Korean and American. The subjects of this study were first-grade and second-grade at one university in Chungbuk, Korea and one university in Texas, USA. The survey study investigated from May 7, 2019 to May 28, 2019. As a result, first, these college students in both countries used the internet the most as them, but the percentage of information collected through textbooks was significantly higher among American college students. Second, Korean college students had a higher level of reliability in information sources than American college students in the order of internet, newspapers, and social network service (SNS), except government prints. Third, American college students had significantly higher satisfaction in major selection than Korean college students. Fourth, Korean college students were helped to select majors through various information sources, especially, the correlation coefficient between SNS was significantly higher.

• Journal of the Korea Society of Computer and Information
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• v.25 no.6
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• pp.81-89
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• 2020

Online reviews we encounter commonly on SNS, although a complex range of assessment information affecting the consumer's preferences are included, it is general that such information is just provided by simple numbers or star ratings. Based on those review types, it is not easy to get specific information that consumers want and use it to make a decision for purchase. Therefore, in this study, we propose a prediction methodology that can provide ratings broken down by evaluation items by performing sentiment analysis on restaurant reviews written in Korean. To this end, we select 'food', 'price', 'service', and 'atmosphere' as the main evaluation items of restaurants, and build a new sentiment dictionary for each evaluation item. It also classifies review sentences by rating item, predicts granular ratings through sentiment analysis, and provides additional information that consumers can use to make decisions. Finally, using MAE and RMSE as evaluation indicators it shows that the rating prediction accuracy of the proposed methodology has been improved than previous studies and presents the use case of proposed methodology.