• Proceedings of the Korean Society of Computer Information Conference
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• 2015.07a
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• pp.149-150
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• 2015

게임 앱은 현재 앱 시장에서도 상위를 차지하는 분류 중에 하나이다. 게임을 앱 사용자에게 널리 이용하게 하기 위해서는 게임이 재미있고, 쉽게 접근할 수 있어야한다. 본 프로젝트에서는 인기리에 방영한 TV프로그램인 '더 지니어스'에 나온 보드게임들 중 1vs1(데스매치) 게임중 레이저장기, 결합, 인디언홀덤, 십이장기, 기억의 미로, 혹과 백을 온라인 안드로이드 모바일 게임으로 구현하였다. 게임을 만들기 위한 툴로는 세계적인 게임 개발 엔진으로 사용되고 있는 유니티(Unity)를 사용하였다. 유니티는 멀티플랫폼 3D/2D 게임 및 인터랙팁브(interactive) 콘텐츠를 말들 수 있는 개발 엔진이다. 본 프로젝트는 오목, 체스 등과같이 누구나 가볍게 즐길 수 있는 2인 실시간 보드게임으로 '더 지니어스'를 통해 게임을 접한 사람들의 흥미를 이용하여 쉽게 다가갈 수 있을 것이다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.619-620
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• 2023

본 논문에서는 탄소중립 중요성이 증대됨에 따라 일상 배출되는 생활 쓰레기 중 자원으로 재활용 할 수 있는 다양한 요소를 탄소중립실천요소로서 정의하고 각 행위를 자동적으로 분류하고자 한다. 딥러닝과 영상처리의 한 분야인 객체 인식 기술을 활용하여, 실시간으로 탄소중립실천요소를 인식하고 재활용 자원의 결과를 수집, 관리할 수 있는 모바일 앱 개발한다. 아울러, 플라스틱컵, 유리컵, 텀블러, 종이컵, 빨대 등 실제 재활용 자원의 이미지에 적용하여 인식을 수행하고 그 결과를 분석한다.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.30-40
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• 2021

Ratings and reviews, despite their growing influence on restaurants' sales and reputation, entail a few limitations due to the burgeoning of reviews and inaccuracies in rating systems. This study explores the texts in reviews and ratings of a delivery application and discovers ways to elevate review credibility and usefulness. Through a text mining method, we concluded that the delivery application 'Yogiyo' has (1) a five-star oriented rating dispersion, (2) a strong positive correlation between rating factors (taste, quantity, and delivery) and (3) distinct part of speech and morpheme proportions depending on review polarity. We created a chicken-specialized negative word dictionary under four main topics and 20 sub-topic classifications after extracting a total of 367 negative words. We provide insights on how the research on delivery app reviews should progress, centered on fried chicken reviews.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.4
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• pp.817-827
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• 2015

In this modern society, people are having a close relationship with smartphone. This makes easier for hackers to gain the user's information by installing the malware in the user's smartphone without the user's authority. This kind of action are threats to the user's privacy. The malware characteristics are different to the general applications. It requires the user's authority. In this paper, we proposed a new classification method of user requirements method by each application using the Principle Component Analysis(PCA) and Probabilistic K-Nearest Neighbor(PKNN) methods. The combination of those method outputs the improved result to classify between malware and general applications. By using the K-fold Cross Validation, the measurement precision of PKNN is improved compare to the previous K-Nearest Neighbor(KNN). The classification which difficult to solve by KNN also can be solve by PKNN with optimizing the discovering the parameter k and ${\beta}$. Also the sample that has being use in this experiment is based on the Contagio.

• The Journal of Society for e-Business Studies
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• v.16 no.4
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• pp.173-195
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• 2011

The ability of offering various and abundant mobile applications has emerged as the knowledge of the smartphone has grown in the smartphone market. The mobile application market has emerged as a competitive new market with enormous potential. Although many users download paid or free mobile applications through the app markets such as the Appstore, there is no significant research regarding customer's application purchase yet. Hence, we refer to the purchase motivation of mobile applications among experienced users who have bought paid applications. We conducted the interview with 30 users and suggest four categories of applications (productivity, entertainment, information, and social networking) and also classify the purchase intentions on each category based on the ground theory. The comparison analysis of the interview provides us what factors affect the application purchase. This framework may advance effective mobile application business model development, implicate the strategy for boosting mobile application market.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.36-38
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• 2021

스마트폰의 다양한 사진들은 현재 대부분 저장 일자를 기준으로 표시되기 때문에 특정 사진을 검색할 경우 많은 노력이 필요하다. 이를 해결하기 위하여 몇몇 앨범형 앱들이 개발되었지만 실제 사용자가 직접 사진을 선택해야 하는 문제점이 존재한다. 이를 해결하기 위하여 본 논문에서는 사진들의 특징을 이용하여 사진의 자동으로 분류가능한 앱의 개발에 대하여 설명한다. 개발된 앱은 위치 및 인물에 따라 현재 사진들을 자동으로 분류하고 폴더에 저장함으로써 보다 쉽게 사진을 관리 할 수 있다. 제안된 기능은 안드로이드 기반으로 개발되었고 각 기능이 정상적으로 동작함을 실험을 통하여 증명하였다.

• The Journal of Society for e-Business Studies
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• v.24 no.2
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• pp.1-14
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• 2019

Because of the characteristics of game software, it is important to quickly identify and reflect users' needs into game software after its launch. However, most sites such as the Google Play Store, where users can download games and post reviews, provide only very limited and ambiguous classification categories for game reviews. Therefore, in this paper, we develop an automatic classification system for game reviews that categorizes reviews into categories that are clearer and more useful for game providers. The developed system converts words in reviews into vectors using word2vec, which is a representative word embedding model, and classifies reviews into the most relevant categories by measuring the similarity between those vectors and each category. Especially, in order to choose the best similarity measure that directly affects the classification performance of the system, we have compared the performance of three representative similarity measures, the Euclidean similarity, cosine similarity, and the extended Jaccard similarity, in a real environment. Furthermore, to allow a review to be classified into multiple categories, we use a threshold-based multi-category classification method. Through experiments on real reviews collected from Google Play Store, we have confirmed that the system achieved up to 95% accuracy.

• Proceedings of the Korea Information Processing Society Conference
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• 2011.11a
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• pp.645-647
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• 2011

본 논문에서는 최근 각광받고 있는 스마트폰 증강현실 서비스의 구현방법을 소개한다. 스마트폰에서 다양한 애플리케이션에 증강현실 기법이 적용되고 있다. 본 연구에서는 안드로이드 기반 스마트폰 애플리케이션으로 증강현실을 구현하는 테크닉에 대하여 소개한다. 일반적으로 증강현실 애플리케이션은 스마트폰 앱(app)개발 분야에서는 다소 난이도가 있는 응용으로 분류된다. 따라서, 증강현실 엔진을 구현한 외부 라이브러리를 활용하는 형태로 개발하는 경우가 많은데, 본 연구에서는 이러한 증강현실 라이브러리를 적용하지 않더라도 증강현실 애플리케이션을 직접 개발할 수 있도록 관련 실무기술을 소개하고 널리 보급하는데 목적을 둔다.

• 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.

• Journal of Industrial Convergence
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• v.15 no.2
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• pp.27-36
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• 2017

In this study, we analyzed service quality factors of O2O delivery app based on Kano model and survey, and classified service quality into several dimensions. As a result of the analysis, the one dimensional quality factors were accurate information transmission, variety of restaurants, diversity of payment methods, diversity of menu selection, discomfort resolution, kindness of service, taste and quality of food, hygiene and cleanliness, Attractive quality factors such as updated information, reliable reviews, various ordering methods, fast delivery, brand image, discount point payment and accumulation. Although the must-be quality factor did not appear, it turned out that the discomfort resolution was close to the must-be quality factor. The indifferent quality factors were informational services, events and promotions. The O2O delivery app market is continuing to grow and competition is getting more and more intense. The results of this study will help O2O delivery app vendors to establish strategies to focus on certain quality of service factors.