• Journal of Digital Contents Society
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• v.19 no.8
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• pp.1433-1442
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• 2018

This study develops and improves the EZ Touch App of the scorecard application (app) using the smartphone and the pad, and works with the customer management system (C/S). The research was conducted as follows. First, how do you handle the EZ Touch input method on a scorecard? Second, how to configure the platform of customer (member) management system (C/S) and data server system? Third, does EZ Touch App work organically with customer management system (C/S)? The developed EZ Touch is entered into the scorecard as an input method using the gesture as a result of this research, and it is linked with the C/S system to organize the review function, hall information function, field coaching function through score, It can be used for applications such as information management functions and statistics through differentiated statistics. However, there are some problems and improvements in user convenience in real time use. I think there is a need to study to solve this problem in the future. EZ Touch input method is input to the scorecard by inputting gesture of the finger as a result of this study, and it is linked with this, and it is possible to use differentiated statistics such as review function, hall information function, field coaching function, It is the purpose of the study to improve the technical competitiveness of the product by developing the application.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.1
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• pp.41-54
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• 2020

In this paper, it will study various problems such as personal information infringement from when using various useful Apps in the Smartphone environment. It also researched the vulnerabilities Mobile Apps and the risks of personal information leakage when using Smartphone information to decrease threat and find solution. In the second chapter, it will check the existing Mobile App related Apps. In the third chapter, it will check the threats and major factors that caused by the leakage of personal information which related to the app. Then it will suggest solution and end with conclusion. This paper also looked at various problems that caused by illegal adverse effect from illegal personal information collection. Then it researched and made suggestion to make consideration on safety of personal information and privacy infringement that threat to personal information For safety of mobile banking, it proposed a safety method to separate and manage the code which has the core logic which required to run the App. For safety of direction App, when running the direction App, even if the information is collected, location information for unauthorized accessed will encrypt and store in DB, so that access to personal information is difficult. For delivery App environment, by using the national deliver order call center's representative phone to receive a telephone order then, the customer information is delivered to the branch office when it receive order and it will automatically delete information from the server when the delivery is completed by improving DB server of order. For the smart work app environment, the security solution operates automatically by separating and make independent private and work areas. Then it will suggest initialization for company's confidential business information and personal information to safe from danger even if loss.

• Korean Journal of Clinical Pharmacy
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• v.33 no.1
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• pp.51-61
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• 2023

Background: Mobile applications (apps) on dietary supplements can increase consumers' access to information. However, it can lead to indiscriminate use of dietary supplements. This study aims to systematically review dietary supplement apps released in English and Korean and evaluate the quality of those apps. Methods: Through the app stores, apps on dietary supplements were systemically searched and examined. Two independent evaluators evaluated the apps and presented a mean score using the Mobile App Rating Scale (MARS). The correlation between MARS scores, user and evaluator ratings, and the number of secondary features of the apps were analyzed. Results: Of the 2,772 dietary supplement apps identified, 17 apps were included according to the selection criteria. The mean MARS score was 3.28 (standard deviation: 0.29) out of 5. Apps had higher scores in aesthetics and functionality dimensions, while engagement and information dimensions had lower scores. There was a positive correlation between the number of app downloads and information among MARS dimensions. The subjective evaluation also correlated with the information dimension. There was a positive correlation between the secondary features of the apps and MARS total score as well as the engagement dimension. Conclusion: The dietary supplement apps need to be managed at a higher level of quality to provide safe and reliable information to consumers. Especially, quality on information and engagement dimensions can be improved. Involvement of healthcare professionals in the app development, management with adequate referencing of information, and use of secondary features for enhanced user engagement can be helpful.

• Korean Journal of Acupuncture
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• v.40 no.1
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• pp.1-12
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• 2023

Objectives : This study aims to provide information regarding the status and quality of mobile applications (MAs) using self-acupressure by performing a systematic review. Methods : We conducted comprehensive searching on five international databases and two app markets from inception to July 31, 2022 to identify MAs using self-acupressure. We analyzed the characteristics of each MA regarding the name of the MA, registered app markets, target symptoms, developers, the year and country of development, cost, target age, media function, and expertise. We assessed the quality of each MA using Mobile Application Rating Scale (MARS). Results : We identified a total of 30 MAs using self-acupressure (25 MAs from the app market and 6 MAs from clinical studies, with 1 MA in common). 17 out of 24 MAs from the app market provided self-acupressure regimens for various symptoms and the others provided regimens for specific symptoms such as memory, anxiety, depression, asthma, allergy, low back pain, and headache. 14 developers were reported. 23 MAs were developed after 2013. The largest number of MAs were developed in the United States. The target age group of 12 MAs was above the age of 3, and that of 11 MAs was above the age of 12. 14 MAs provided multimedia functions such as videos. 13 MAs provided information of expertise. From clinical studies, only 3 out of 6 MAs were accessible through the app market. 4 MAs were developed by the researchers of the study. In terms of MARS, the score of MAs from the app market was higher than that of MAs from clinical studies in both objective and subjective evaluation areas. Conclusions : This study summarizes the characteristics of MAs using self-acupressure. More MAs using self-acupressure should be developed and further clinical research for MA on each symptom and disease is warranted for the diversification of MA fields using self-acupressure.

• 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.

• Journal of Intelligence and Information Systems
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• v.21 no.2
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• pp.1-18
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• 2015

Collaborative filtering(CF) algorithm has been popularly used for recommender systems in both academic and practical applications. A general CF system compares users based on how similar they are, and creates recommendation results with the items favored by other people with similar tastes. Thus, it is very important for CF to measure the similarities between users because the recommendation quality depends on it. In most cases, users' explicit numeric ratings of items(i.e. quantitative information) have only been used to calculate the similarities between users in CF. However, several studies indicated that qualitative information such as user's reviews on the items may contribute to measure these similarities more accurately. Considering that a lot of people are likely to share their honest opinion on the items they purchased recently due to the advent of the Web 2.0, user's reviews can be regarded as the informative source for identifying user's preference with accuracy. Under this background, this study proposes a new hybrid recommender system that combines with users' review mining. Our proposed system is based on conventional memory-based CF, but it is designed to use both user's numeric ratings and his/her text reviews on the items when calculating similarities between users. In specific, our system creates not only user-item rating matrix, but also user-item review term matrix. Then, it calculates rating similarity and review similarity from each matrix, and calculates the final user-to-user similarity based on these two similarities(i.e. rating and review similarities). As the methods for calculating review similarity between users, we proposed two alternatives - one is to use the frequency of the commonly used terms, and the other one is to use the sum of the importance weights of the commonly used terms in users' review. In the case of the importance weights of terms, we proposed the use of average TF-IDF(Term Frequency - Inverse Document Frequency) weights. To validate the applicability of the proposed system, we applied it to the implementation of a recommender system for smartphone applications (hereafter, app). At present, over a million apps are offered in each app stores operated by Google and Apple. Due to this information overload, users have difficulty in selecting proper apps that they really want. Furthermore, app store operators like Google and Apple have cumulated huge amount of users' reviews on apps until now. Thus, we chose smartphone app stores as the application domain of our system. In order to collect the experimental data set, we built and operated a Web-based data collection system for about two weeks. As a result, we could obtain 1,246 valid responses(ratings and reviews) from 78 users. The experimental system was implemented using Microsoft Visual Basic for Applications(VBA) and SAS Text Miner. And, to avoid distortion due to human intervention, we did not adopt any refining works by human during the user's review mining process. To examine the effectiveness of the proposed system, we compared its performance to the performance of conventional CF system. The performances of recommender systems were evaluated by using average MAE(mean absolute error). The experimental results showed that our proposed system(MAE = 0.7867 ~ 0.7881) slightly outperformed a conventional CF system(MAE = 0.7939). Also, they showed that the calculation of review similarity between users based on the TF-IDF weights(MAE = 0.7867) leaded to better recommendation accuracy than the calculation based on the frequency of the commonly used terms in reviews(MAE = 0.7881). The results from paired samples t-test presented that our proposed system with review similarity calculation using the frequency of the commonly used terms outperformed conventional CF system with 10% statistical significance level. Our study sheds a light on the application of users' review information for facilitating electronic commerce by recommending proper items to users.

• International Journal of Knowledge Content Development & Technology
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• v.11 no.1
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• pp.85-111
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• 2021

This study aims to analyze users' assessment of electronic libraries in the mobile app market and promote service improvement based on this. To this end, the basic background and purpose of the research, research method, and research scope were first set, and the relevant literature and empirical prior studies were analyzed. Next, users' evaluations of electronic libraries were collected and analyzed from Google Play Store. Based on the results analyzed, measures to improve the quality of electronic libraries were discussed. Based on the results of the study, the following improvement measures are proposed. Need for systemic improvement and stabilization. Provision of applications suitable for multi-device environments. Resumption of services after systematic inspection after updating. Simplification of sign up, log in, and authentication procedures. User support through real-time chat. Introduction of a detailed assessment of reviews. Provision of guidance and user manual for electronic libraries. Improvements to expand user convenience, and Securing differentiation from other similar services.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.22 no.1
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• pp.171-191
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• 2011

The purpose of this study is to introduce the concepts of smartphone and app, to review the theoretical researches and the representative service examples in academic libraries' mobile services based on smartphone apps, and to propose the proper mobile services methods based on smartphone apps in academic libraries of Korea. The ways for mobile app services in academic libraries are like these: 1) Libraries need to prepare the hybrid service system based on the combination of mobile web and app for smartphone. 2) Libraries have the guidelines for choosing apps which are applied to library services. 3) Libraries develop the apps for library marketing and education services and make use of existed apps to their own services. 4) Smartphone application bibliography service(Appography service) needs to be developed and serviced as an academic library service field.

• Journal of Internet Computing and Services
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• v.20 no.3
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• pp.111-117
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• 2019

We categorize the model of simple payment into Magnetic Secure Transmission, Near Filed Communication, and App Card based on the Focus Group Interview. We also define the key drivers for the diffusion of simple payment services based on the literature review with the experts. Through Analytic Hierarchy Process our finding suggests that the degree of acceptance at the stores is the most critical factor which decides the diffusion of simple payment service model. Security is also the important driver but due to the fact that service providers should follow the information security rule and supervisory guidance, it actually did not make a big difference in terms of assessing competence of each model.

• The Journal of the Korea Contents Association
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• v.19 no.5
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• pp.249-258
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• 2019

Currently, people are paying more attention to smart home businesses. Therefore, the research on smart home system is becoming important. Smart Home App, which is an important component of smart home system, needs to consider the development of evaluation indicators for usability. In this regard, this paper takes smart home App as the object to develop the usability evaluation indicators of smart home App design. For this purpose, this study performed three rounds of survey by using the Delphi method. In the first round, 8 suitable areas were selected by collecting opinions from experts and analyzing the Content Validity Ratio, which was derived from literature review. Based on the results of the first survey, a total of 38 evaluation items were collected through prior research and user interview surveys. For the 38 collected evaluation items, 27 evaluation items have been selected by analyzing Average Value, Standard Deviation, Content Validity Ratio, Consultation and Convergence in the second and third rounds. The result of this study can be used as a guideline when evaluating the usability of smart home App design.