APP 분석 시스템 및 CMS시스템 오픈API 개발

김성림,박형록,전수진 (사)디지털산업정보학회 2014 디지털산업정보학회논문지 Vol.10 No.3

The smart phone are changing the way people communicate. And, the mobile app marketplace is greatly fast-growing. The app store continues its rapid growth, there are already more than 900,000 mobile apps on AppStore. We anticipate to see gained momentum throughout the business. Mobile is also becoming popular for marketers. Therefore, specialized app analysis systems are becoming important to how marketers and app developers invest, analyze and market their apps. App analysis systems enable users to discover and analyze behavior through data observations and meaningful patterns. In this paper, we introduce app analysis system and CMS System Open API, NugaLog. The NugaLog acquires users data and engages with them in a variety of ways. It will be essential for us to understand how users interact with and move through the app. The NugaLog will be able to see the number of users, smart phone model, smart phone OS, resolution, page views, and app version.

교사의 권위 분석 : Parsons, Keddie, Apple의 연구를 중심으로

김성림 숙명여자대학교 교육문제연구소 1994 교육연구 Vol.3 No.-

컨텍스트 인식 환경에서 차별화된 권유를 사용한 프로액티브 모바일 커머스 서비스

김성림,권준희 대한전자공학회 2006 電子工學會論文誌 IE (Industry electronics) Vol.43 No.1

According to the growth of wireless networks, and the spread of mobile devices, the provision of recommender services to help consumers find items to purchase with the use of the suited contexts is an important issue in mobile commerce. In this paper, we propose a proactive mobile commerce service that enables a consumer to obtain relevant information efficiently by using differentiated recommendation in context-aware environment. This paper describes the recommendation method and presents grocery shopping application prototype that implement the method. Several experiments are performed and the results verify that the proposed method's recommendation performance is better than other existing methods. 무선 기술의 빠른 발달과 이동통신 사용자의 급증으로 모바일 커머스에서 각 소비자들에게 컨텍스트에 맞게 효과적으로 정보를 권유하는 서비스의 필요성이 점차 부각되고 있다. 본 논문에서는 컨텍스트 인식환경에서 모바일 커머스 서비스를 위한 차별화된 프로액티브 권유 기법을 제안한다. 제안한 기법에서는 컨텍스트에 따라 한번에 모든 정보를 권유하지 않고 레벨별로 차별화하여 프로액티브하게 권유하고, 소비자의 패턴과 프리패칭 기법을 사용함으로써 효율적인 권유 서비스가 가능하다. 이를 위해 제안된 기법을 설명하고 이를 모바일 커머스 어플리케이션 프로토타입에 적용해본다. 또한, 실험을 통해 기존 기법보다 제안된 기법이 우수함을 보인다.

소셜 사물인터넷에서 소셜 관계를 이용한 사물 추천 기법

김성림,권준희 (사)디지털산업정보학회 2014 디지털산업정보학회논문지 Vol.10 No.3

The Internet of Things(IoT) is a new promising technology made from a variety of technology. The IoT links the objects or people, then enabling anytime, anywhere connectivity for anything and not only for anyone. Social networking services have changed the way people communicate. Recently, new research challenges in many areas of Internet of things and social networking services are fired. In this paper, we propose things recommendation method using social relationship in social Internet of Things. We study previous researches about social network service, IoT, and social IoT. We proposed SIoT_FW(Social IoT Friendship Weight) using static and a dynamic social friendship weight. Also, our method considers four social relationships (Ownership Object Relationship, Co-Location Object Relationship, Social Object Relationship, Parental Object Relationship). We presents a music device scenario using our proposed method.

A Study on Recommendation Method Based on Web 3.0

김성림,권준희 (사)디지털산업정보학회 2012 디지털산업정보학회논문지 Vol.8 No.4

Web 3.0 is the next-generation of the World Wide Web and is included two main platforms, semantic technologies and social computing environment. The basic idea of web 3.0 is to define structure data and link them in order to more effective discovery, automation, integration, and reuse across various applications. The semantic technologies represent open standards that can be applied on the top of the web. The social computing environment allows human-machine co-operations and organizing a large number of the social web communities. In the recent years, recommender systems have been combined with ontologies to further improve the recommendation by adding semantics to the context on the web 3.0. In this paper, we study previous researches about recommendation method and propose a recommendation method based on web 3.0. Our method scores documents based on context tags and social network services. Our social scoring model is computed by both a tagging score of a document and a tagging score of a document that was tagged by a user’s friends.

산모와 태아에서 동시에 발견된 Bochdalek Hernia 1례

김성림,조대현,김종옥,이승호 대한산부인과학회 1989 대한산부인과학회 학술대회 Vol.63 No.-

Recommendation Method for Social Service in Ubiquitous Environment

김성림,권준희 (사)디지털산업정보학회 2011 디지털산업정보학회논문지 Vol.7 No.2

Recent development of information technologies produces a lot of community services. Social Network Service is one of the community services on the world wide webs. In the Social Network Service, a user can register other users as friends and enjoy communication through a virtual message. Previous researches show a few social service methods using manually generated tagging. However, the manual social tagging is not widely used in many social network services. Moreover, they do not consider ubiquitous computing environment. We propose a recommendation method for social service using contexts in ubiquitous environment. Our method scores documents based on context tags and social network services. Our social scoring model is computed by both a tagging score of a document and a tagging score of a document that was tagged by a user’s friends.

소셜 데이터를 위한 효율적인 데이터 처리 기법

김성림,권준희 (사)디지털산업정보학회 2013 디지털산업정보학회논문지 Vol.9 No.3

The evolution of the Web from Web 1.0 to Web 2.0 has brought up new platforms as SNSs(Social Network Service) that are used by users to articulate and manage their relationships. SNSs are an online phenomenon which has become extremely popular. A SNS essentially consists of a representation of each user, his/her social links, and a variety of additional services. SNSs are increasingly attracting the attention of academic and industry researchers. What makes SNS unique is that they have a relationship with friends. The friend recommendation is one important feature of social networking services. People tend to trust the opinions of friends they know rather than the opinions of strangers. In this paper, we propose an efficient data processing method for social data. We study previous researches about social score in social network service. Our ESS(Efficient Social Score) is computed by both friendship weight and score of a document that was tagged by a user’s friends. Our experimental results also confirm that our method has good performance.

사물인터넷에서 소셜 네트워크 사용자 친밀도를 이용한 점진적 검색 기법

김성림,권준희 (사)디지털산업정보학회 2018 디지털산업정보학회논문지 Vol.14 No.3

Social network services allow you to share your thoughts and preferences more easily. They share your views with a large number of people who are friends with you without restriction of time or place. In the IoT environment, the amount of data is massively increasing as social network services spread rapidly. This change in the environment is driving the need for research into new retrieval methods that are different from conventional retrieval methods. In this paper, we propose a progressive retrieval method using the intimacy of social network users in the IoT. The first thing is to extract the user with the highest intimacy by using the property that the number of the owner of the information stored in the IoT environment is small. By accessing information in objects owned by these extracted users, the amount of information retrieved is reduced. It also improves retrieval efficiency by gradually retrieving information according to the user's level of interest. We present a new retrieval method and algorithm. The scenario also illustrates the effectiveness of the proposed method.

상황 인식 환경에서 온톨로지를 이용한 프로액티브 검색 기법

김성림,권준희 대한전자공학회 2007 電子工學會論文誌-CI (Computer and Information) Vol.44 No.3

The context-aware environment focuses on recognizing the context and physical entities. For this reason, there has been an increasement in research of context-aware computing environment. Ontology-based context models are widely used in ubiquitous environment because of context sharing and reusing. In this paper, we propose a proactive retrieval method using ontology in context-aware environment. The method use a concept level of hierarchical concept tree in ontology for more efficient retrieval. This paper describes the proactive retrieval method and ontology model. Several experiments are performed and the results verify that the proposed method's efficiency is better than other existing methods. 상황 인식 환경에서는 물리적인 환경, 상황 등을 시스템이 인식하고 이를 기반으로 사용자와의 상호작용을 지원하는 상황 인식 기술이 중요한 요소로 자리잡고 있다. 온톨로지 기반의 상황 정보 모델은 상황정보의 공유와 재사용의 이점을 제공하기 때문에 최근 널리 사용되고 있다. 본 논문에서는 상황 인식 환경에서 온톨로지를 이용한 새로운 프로액티브 검색 기법을 제안한다. 제안된 기법은 온톨로지의 계층적 개념 트리를 이용하여 사용자의 상황에 맞는 정보의 개념 수준을 결정함으로써 보다 효율적인 검색이 가능하다. 이를 위해 제안된 기법을 설명하고, 실험을 통해 기존 기법보다 제안 기법이 우수함을 보인다.