• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.2
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• pp.125-132
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• 2017

O2O service contribute to sales increment by marketing of offline store using online. In particular, O2O business allowed various services by smart-phone due to rapid increase of mobile device use and various services depend on customer's location. This O2O service play major roll in real purchase making of offline store. In smart-phone apps. development for O2O service, recent an Object-oriented Analysis and Design Method, that is, UML is more useful method than Structured Analysis and Design Method. Therefore in this paper, Software analysis and design method which is smart-pone app. for O2O restaurant service is presented. Also it shows that this analysis/design method is very useful for the Restaurant O2O Commercial System production.

• Journal of Digital Contents Society
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• v.19 no.4
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• pp.631-637
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• 2018

In order to read newspaper articles, the use of paper newspapers is decreasing and smartphone are increasingly used. As a result, the number of news apps continues to increase. Many of the news apps in the Android Play Store fall into two categories. The first is an app that is developed by a specific newspaper company and distributes only the articles of the newspaper company. The rest is an app that shows a list of newspapers and shows the homepage when a newspaper is selected. In this paper, we have designed and implemented a Real-Time News app for collecting articles from many newspapers and providing them in real time. Newspapers provide up-to-date articles with RSS feeds. The server program stores them in the DB, and transmits the articles requested in the Real-Time News app in real time. In order to see the latest news, it is possible to collect the articles of each newspaper without visiting the websites of the various newspapers, and it is possible to reduce the mobile data usage used to access each website.

• Journal of the Korean Society of Costume
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• v.67 no.1
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• pp.40-55
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• 2017

The current new distribution environment provides the consumers to shop at anytime and any places by using mobile appliances. So, the companies which run the offline-store increase the contact point with the consumer by launching not only online-store but also the mobile application (app). Moreover, they are trying to operate the Omni-channel shopping environment. In order for this research to draw the direction of 'the Omni-Channel Strategy', which is about the changed distribution environment of the domestic fashion enterprise, the following steps were performed. First of all, the term related to 'Omni-Channel' is defined. And then, Example of the 'Omni-Channel' strategy and 'O2O' business in the domestic distributior were researched. Lastly, present condition of the 'Omni-Channel' strategy case of the domestic fashion industry was researched. At the result, the online-stores usually have several brands which can not represent their identities. It is suggested that each online-store according to each brand has their own characteristic identity. And The Omni-Channel strategy of the domestic fashion enterprise that is needed the connection point connecting the on-line and off-line. It is able to allure the customer to the off-line-store.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.1
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• pp.17-24
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• 2023

Mobile apps frequently request permission to access sensitive data for user convenience. However, while using mobile applications, sensitive and personal data has been leaked even if users do not allow it. To deal with this problem, Google App Store has required developers to disclose how the mobile app handles user data in a privacy policy. However, users are not certain that the privacy policy describes all the app's behavior. They have no choice but to rely on the privacy policy to confirm how the app uses data. This study designed a system that checks the reliability of privacy policies by analyzing the privacy policy texts and mobile apps. First, the system extracts and analyzes the privacy policy texts to check which personal data the privacy policy discloses that the mobile apps can collect. After analyzing which data apps can access using android static analysis, we compare both results to analyze the reliability of privacy policies. For the experiment, we collected the APK files and metadata of about 13K android apps registered in the Google Play Store and preprocessed the apps by four conditions. According to the comparison between privacy policies and mobile app behavior, many apps can access more personal data than disclosed in the privacy policy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.2C
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• pp.119-131
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• 2012

Recently smart phones have been proliferating widely and quickly. Since the number of mobile apps that are being developed and deployed to domestic/international app stores is rising, more apps are being installed and deleted by users without any difficulty. The deployed apps are each attested through distinct verification framework of specific app stores. However, such verification frameworks are insufficient in checking security concerns. Unfortunately, the security verification framework is necessary since the incidents of leaking privacy and confidential information are being increased in lately. The aim of this paper is to provide the security verification framework that assures security and reliability of the e-government mobile apps. In order to verify proposed verification framework, a few apps were selected and inspected through proposed framework and these inspection results are included in this paper.

• The Journal of the Korea Contents Association
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• v.10 no.12
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• pp.129-136
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• 2010

Smartphone used to be an it item for only business people and early adaptors. However, the public interest towards Smartphone has been rapidly increased and now is spreading to the everyday life in general people. Variety of applications are introduced and registered in a day, but there are not enough apps with simple and useable interface. This is because that the applications are developed only in a view from developer and designer to match the splendor design and technical skills of apps not concerning the users. Therefore this study will analyze the value in use and design trend of registered apps in apps store to recognize the importance in use and also to discuss about a plan to apply this into the apps more effectively. In order to improve the mobile app usability, this study suggest that using intuitional icon, designing easy to use app navigation. This will lead to produce clear instruction for app developers and designers with more reliable effects in the future of Smartphone world.

• Journal of Fashion Business
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• v.17 no.4
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• pp.149-163
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• 2013

This study investigated the effects of smart phone usage motives and fashion brand app factors upon the intention to accept fashion brand applications. Data were collected from 250 female college students living in Seoul and Gyeonggi-do. 220 reliable data were analyzed by frequency, factor analysis, Cronbach's alpha, ANOVA,, Duncan test, paired t-test, chi-square analysis, regression. The results were as follows: Firstly, the 'information acquisition' and the'use of time' were considered to be the most important motive factors driving consumer's smart phone usage. Secondly, the motives underpinning smart phone user's intention to accept a fashion brand application were 'social relationships', 'entertainment', and 'information acquisition'. Thirdly, the frequently used factors during the usage of fashion brand application could be classified in order of frequency as follows: 'product information provision', 'store information provision', 'coordinated information provision', 'fashion information provision', 'entertainment provision', 'hobbies and life information provision', virtual wearing provision', 'SNS provision', and, 'events and coupons provision'. Fourthly, a factor analysis of these nine factors were classified into 'basic information type', and 'additional information type'. The influences of basic information type and the additional information type upon the intention to accept the fashion brand application showed the following significant result: The basic information type had a greater influence upon the intention to accept the fashion brand app.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1445-1452
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• 2016

Recently Mobile Software Applications are developed in various languages and stored in App Store. App Users selectively use appropriate apps for the owned hardware. In other words, it depends on the kinds of operating systems of the apps whether to use or not to use the applications in various languages. The apps should be differently implemented according to the kind of the user's device, though they provide the same functions. To solve these problems, it is necessary to define an independent function specification method which is not dependent to a specific system environment. In this paper, the Mobile Application Developing Framework is suggested, which incorporates all of the development process. Standardized models are proposed which can be used in the analysis and design steps. In implementation phase, a technique for cross framework design is suggested so as to implement a platform dependent mobile app.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.2_2
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• pp.445-456
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• 2024

This study aims to suggest service improvement opportunities by analyzing user review data of the top three OTT service apps(Netflix, Coupang Play, and TVING) on Google Play Store. To achieve this objective, we proposed a framework for uncovering service opportunities through the analysis of negative user reviews from OTT service providers. The framework involves automating the labeling of identified topics and generating service improvement opportunities using topic modeling and prompt engineering, leveraging GPT-4, a generative AI model. Consequently, we pinpointed five dissatisfaction topics for Netflix and TVING, and nine for Coupang Play. Common issues include "video playback errors", "app installation and update errors", "subscription and payment" problems, and concerns regarding "content quality". The commonly identified service enhancement opportunities include "enhancing and diversifying content quality". "optimizing video quality and data usage", "ensuring compatibility with external devices", and "streamlining payment and cancellation processes". In contrast to prior research, this study introduces a novel research framework leveraging generative AI to label topics and propose improvement strategies based on the derived topics. This is noteworthy as it identifies actionable service opportunities aimed at enhancing service competitiveness and satisfaction, instead of merely outlining topics.

• Smart Media Journal
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• v.13 no.6
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• pp.35-43
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• 2024

During the post-pandemic period, the interest in foreign language learning surged, leading to increased usage of language-learning apps. With the rising demand for these apps, analyzing app reviews becomes essential, as they provide valuable insights into user experiences and suggestions for improvement. This research focuses on extracting insights into users' opinions, sentiments, and overall satisfaction from reviews of HelloTalk, one of the most renowned language-learning apps. We employed topic modeling and emotion analysis approaches to analyze reviews collected from the Google Play Store. Several experiments were conducted to evaluate the performance of sentiment classification models with different settings. In addition, we identified dominant emotions and topics within the app reviews using feature importance analysis. The experimental results show that the Random Forest model with topics and emotions outperforms other approaches in accuracy, recall, and F1 score. The findings reveal that topics emphasizing language learning and community interactions, as well as the use of language learning tools and the learning experience, are prominent. Moreover, the emotions of 'admiration' and 'annoyance' emerge as significant factors across all models. This research highlights that incorporating emotion scores into the model and utilizing a broader range of emotion labels enhances model performance.