• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.3
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• pp.643-650
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• 2018

This service uses beacon with BLE technology, and USER APP has priority with Anchor IPS which secures location and device. Since then, it has been linked with character beacons that can be used in various places. The character beacon which is recognized as a service is able to confirm the user's location through API key of the LBS CMS server, and receives various contents services of the UESR CMS server. The service network consists of character beacon, Anchor IPS, USER APP, LBS CMS server, and USER CMS server. The purpose of the service is to promote local tourism and local culture to tourists through local unique characters.

• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.321-326
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• 2019

As AI technology is recently introduced into various fields, it is being applied to the fashion field. This paper proposes a system for recommending cody clothes suitable for a user's selected clothes. The proposed system consists of user app, cody recommendation module, and server interworking of each module and managing database data. Cody recommendation system classifies clothing images into 80 categories composed of feature combinations, selects multiple representative reference images for each category, and selects 3 full body cordy images for each representative reference image. Cody images of the representative reference image were determined by analyzing the user's preference using Google survey app. The proposed algorithm classifies categories the clothing image selected by the user into a category, recognizes the most similar image among the classification category reference images, and transmits the linked cody images to the user's app. The proposed system uses the ResNet-50 model to categorize the input image and measures similarity using ORB and HOG features to select a reference image in the category. We test the proposed algorithm in the Android app, and the result shows that the recommended system runs well.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.171-173
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• 2012

광범위한 스마트폰의 보급으로 인해 관련 APP 시장 또한 급격하게 증가하고 있다. 많은 APP이 개발되고 있지만 대부분 특정 분야에 집중되어 있으며 교육용 APP이 시장에서 차지하고 있는 비율은 극히 낮다. 시장 비율이 낮은 이유는 기존 출시된 대다수의 교육용 APP이 가지는 두 문제점 때문이다. 첫 번째는 동일 콘텐츠의 반복학습으로 인해 재사용 빈도가 많이 낮고 자기주도학습 능력을 이끌어 낼 수 없다는 점이며 두 번째는 문제 제공 및 정답 확인의 단순 구조로 되어 있어 사용자가 자신의 수준 및 취약 부분을 분석하기 힘들다는 점이다. 본 논문은 스마트폰 환경에서 앞서 언급한 두 가지 문제점을 해결하기 위해 시스템 구조 변경 없이 콘텐츠 변경이 가능하며 사용자의 수준을 파악할 수 있는 기능을 가진 사용자 맞춤 교육을 위한 교육용 앱 설계에 대하여 제안한다.

• Journal of Broadcast Engineering
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• v.20 no.1
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• pp.110-121
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• 2015

The digital app-book is an advanced form of the electronic book (e-book), which attracts a lot of interests by the help of video, sound, sensors and a variety of interactions. As mobile devices have evolved, the demand of digital app-books is also rising substantially. However, the distribution of digital app-book contents is hard to meet the demand because the digital app-book requires a lot of programming cost for the interaction. To resolve this problem, Was verified and implementation as a library function of the interaction between device and user. The proposed library consists of three parts (user action recognition, device action, and content action) and provides various user-device interaction functions by combining methods of each part, which can support source code reusability, easy understanding and availability, and wide expandibility. The library was used in the development of natural science education app-book contents. As a result, it could reduce a lot of code lines and facilitate more rapid app-book development.

• The Journal of the Korea Contents Association
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• v.17 no.11
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• pp.143-155
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• 2017

In the mobile-first era, plenty of mobile apps have been created so that the number of apps owned in a smartphone have been increasing as well. However, users spend most of time with only a few apps and the rest of apps are just kept in their smartphones for future usage. Thus, in order to help users find the apps quickly it is important to study how users arrange apps in a mobile phone screen and find an app. In the literature, we extracted 5 user types to organize mobile apps. We further conducted user survey with 30 subjects and finalized major 3 user types categorized by relatedness(A), aesthetic(B), and external concepts(C). We found that most of subjects took less than 2 minutes when finding frequently-used-apps. However we identified difference in times taken to find a barely-used-apps across three user types; while A type users turns out to be the most effective in finding barely-used-apps, the B type uses tend to be the least effective among three types. For the A type users, an app's name is more important than an icon image because they tend to guess the functionality from the name of the app. The B type users use the color of app icon to find the app in the smartphone. For the C type users who tend to remain the original position of an app when first downloading it in the smartphone, the visibility of an app icon is important to catch users' eyes while they scan a page. The results of this study is expected to be useful for UX designers who improve the usability of app icon usage considering the user types.

• ETRI Journal
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• v.43 no.1
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• pp.95-108
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• 2021

Application (app) ratings are feedback provided voluntarily by users and serve as important evaluation criteria for apps. However, these ratings can often be biased owing to insufficient or missing votes. Additionally, significant differences have been observed between numeric ratings and user reviews. This study aims to predict the numeric ratings of Google apps using machine learning classifiers. It exploits numeric app ratings provided by users as training data and returns authentic mobile app ratings by analyzing user reviews. An ensemble learning model is proposed for this purpose that considers term frequency/inverse document frequency (TF/IDF) features. Three TF/IDF features, including unigrams, bigrams, and trigrams, were used. The dataset was scraped from the Google Play store, extracting data from 14 different app categories. Biased and unbiased user ratings were discriminated using TextBlob analysis to formulate the ground truth, from which the classifier prediction accuracy was then evaluated. The results demonstrate the high potential for machine learning-based classifiers to predict authentic numeric ratings based on actual user reviews.

• Journal of Information Technology Services
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• v.13 no.3
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• pp.51-76
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• 2014

As the smart phone devices gain popularity, companies no longer consider mobile application marketing as an auxiliary marketing tactic. The branded mobile application (branded app) becomes an important part of marketing strategies. This study is an attempt to investigate antecedents of the use intention of the branded app from the perspective of TAM (Technology Acceptance Model). This study takes a macro perspective in explaining the adoption process by incorporating a set of new, yet promising additional variables into the TAM model such as flow experience, benefits, innovation inclination, and customization features. Data were collected by using a survey research. A total of 270 responses were collected. Questionnaires from 25 individuals were removed from the data set due to the insincere responses, leaving the final sample size of 245. Findings support all but one hypotheses of the study. Both perceived utilitarian benefits and customization features of the branded app were found to have positive influences on the perceived usefulness of the branded app. Also, the innovation inclination and perceived entertainment of branded app users showed positive influences on the perceived ease of use of branded app. In addition, it was shown that the perceived usefulness about the use of the branded app influenced positively the flow experience and the users' attitudes toward branded app. Also, the ease of use perceived by branded app users had positive influences on the perceived usefulness and the user's attitude toward branded app. However, the ease of use of branded app did not have a significant influence on the flow experience among users. Moreover, the flow experience from the use of branded app users influenced positively the user's attitude toward branded app. Finally, the users' attitudes toward branded app had positive influences on their intention to use the branded app. Implications for practitioners and academicians are provided.

• The Journal of Information Systems
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• v.32 no.1
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• pp.147-178
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• 2023

Purpose The mail goal of this study is to find out factors influencing users' satisfaction of public application with the emphasis of service quality of public web and public value. For this purpose, we applied IS success model to develop the research model that explains users's satisfaction and public performance. Design/methodology/approach The proposed research model was developed based on IS success model along with two moderating effects - Service Quality of Public Web and Public Value in order to empirically test proposed causal relationships withing the model. A total of 377 survey responses were analyzed by forming the structural equation modeling with AMOS 24.0. Findings The analysis results show that the service, information, and system quality from IS success model are positively associated with user satisfaction, which in turn is positively associated with public app performance. The results also show that the relationship between user satisfaction and public app performance is positively moderated by public value. However, the relationship between public app service quality and user satisfaction isn't moderated by public web service quality.

• Journal of Korean Society for Quality Management
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• v.40 no.2
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• pp.211-218
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• 2012

Over the last two decades, many information system researchers have developed the variables of information system using the measurement of user satisfaction. In context, this research developed the measurement of user satisfaction in smartphone application market and compared the difference of user satisfaction factors between Adroid market and App store. The results indicated that satisfaction of App store was more than that of Adroid market. The information system and customer-oriented factors of App store were higher than that of Adroid market.

• The Journal of Information Systems
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• v.30 no.4
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• pp.227-245
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• 2021

Purpose The purpose of this study is to examine the variables affecting user satisfaction through previous studies and to examine the differences between apps. Differences are based on factors that determine the quality of real estate service apps and derived by the topic modeling results. Design/methodology/approach This study conducts topic modeling to find factors affecting user satisfaction of real estate service apps using user reviews. Sentiment analysis is additionally conduct on the derived topics to examine the user responses. Findings Users give high sentiment scores for services that can manage factors such as usefulness of information, false sales, and hype. In addition, managing the basic services of app is an important factor influencing user satisfaction.