• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2008년도 춘계학술대회 논문집
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• pp.45-46
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• 2008

• 한국정보기술응용학회:학술대회논문집
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• 한국정보기술응용학회 2007년도 추계 국제학술대회
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• pp.143-143
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• 2007

• 한국데이타베이스학회:학술대회논문집
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• 한국데이타베이스학회 1999년도 춘계공동학술대회: 지식경영과 지식공학
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• pp.95-102
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• 1999

The web-based group collaborative systems are emerging as enterprise-wide information systems. Since data in group collaborative systems are apt to be shared among multiple concurrent users and modified simutaneously by them, the web-based group collaborative systems must support synchronous collaboration in order to provide users with synchronized and consistent views of shared data. This Paper proposes an active web server which can facilitate synchronous collaboration in web-based group collaborative systems. To accomplish such a goal, the active web server manages dependency relationships between shared data and web browsers referencing them and actively propagates changing details of the shared data to all web browsers referencing them. And, this paper examines usefullness and effectiveness of the active web server to apply it to the ball-bearing design example of concurrent engineering design systems. The prototype system of the active web server is developed on a commercial Object-oriented Database Management System (ODBMS) called OBJECTSTORE using the C＋＋ programming language.

• Journal of Information Technology Applications and Management
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• 제26권6호
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• pp.89-101
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• 2019

Many researchers have been focused on designing beauty product recommendation system for a long time because of increased need of customers for personalized and customized recommendation in beauty product domain. In addition, as the application of the deep neural network technique becomes active recently, various collaborative filtering techniques based on the deep neural network have been introduced. In this context, this study proposes a deep neural network model suitable for beauty product recommendation by applying Neural Collaborative Filtering and Generalized Matrix Factorization (NCF + GMF) to beauty product recommendation. This study also provides an implementation of web API system to commercialize the proposed recommendation model. The overall performance of the NCF + GMF model was the best when the beauty product recommendation problem was defined as the estimation rating score problem and the binary classification problem. The NCF + GMF model showed also high performance in the top N recommendation.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2006년도 춘계학술대회 논문집
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• pp.345-346
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• 2006

In the future, a machine will be more improved in the form of advanced concept with collaborative ability in M2M(Machine to Machine, Mobile to Machine) environment for u-Manufacturing system. This paper tried to standardize M2M and design advanced concept machine. The M2M is front-end system for implementing autonomous ubiquitous environment. The advanced machine in M2M will be a collaborative machine with knowledge-evolutionary ability such as u-Machine(Ubiquitous machine), Vortal(Vertical Portal) machine and P2P(Peer to Peer) machine. Such advanced concept machines will be the key subject for M2M cooperation.

• 인터넷정보학회논문지
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• 제19권3호
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• pp.7-14
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• 2018

As SNS(Social Network Service) becomes a part of our life, new information can be derived through various information provided by SNS. Through the public timeline analysis of SNS, we can extract the latest tour trends for the public and the intimacy through the social relationship analysis in the SNS. The extracted intimacy can also be used to make the personalized recommendation by adding the weights to friends with high intimacy. We apply SNS elements such as analyzed latest trends and intimacy to item-based collaborative filtering techniques to achieve better accuracy and satisfaction than existing travel recommendation services in a new way. In this paper, we propose a social travel recommendation system using item - based collaborative filtering.

• Journal of Information Technology Applications and Management
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• 제24권4호
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• pp.1-12
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• 2017

Item-based collaborative filtering (IBCF) is an important technology that is widely used in recommender system of online shopping malls. It uses historical information to compute item-item similarity and make predictions. However, in offline shopping each customer's purchasing pattern can be occurred continuously and repeatedly due to time and space constraints contrast to online shopping. Those facts can make IBCF to have limitations from being applied to offline shopping malls directly. In order to improve the quality of recommendations made by IBCF in offline shopping mall, we propose an ensemble approach that considers both item-item similarity of IBCF and each customer's purchasing patterns which are modeled by item networks. Our experimental results show that this approach produces recommendation results superior to those of existing works such as pure IBCF or bestseller approaches.

• 디지털산업정보학회논문지
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• 제9권1호
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• pp.43-52
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• 2013

Pervasive computing and social network are good resources in recommendation method. Collaborative filtering is one of the most popular recommendation methods, but it has some limitations such as rating sparsity. Moreover, it does not consider social network in pervasive computing environment. We propose an effective proactive friend recommendation method using social network and contexts in pervasive computing environment. In collaborative filtering method, users need to rate sufficient number of items. However, many users don't rate items sufficiently, because the rating information must be manually input into system. We solve the rating sparsity problem in the collaboration filtering method by using contexts. Our method considers both a static and a dynamic friendship using contexts and social network. It makes more effective recommendation. This paper describes a new friend recommendation method and then presents a music friend scenario. Our work will help e-commerce recommendation system using collaborative filtering and friend recommendation applications in social network services.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2002년도 춘계공동학술대회
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• pp.909-915
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• 2002

Collaborative system is an essential idea in the global and e-business environments Workflow plays a key role implementing collaborative system. Workflow is an emerging technology for business process automation, monitoring integrity enforcement, and recovery. A process model describes the structure of business process in the real world The process model can be transformed into a Workflow model utilizing a computer. The paper proposes a web-based Workflow process design in the B2B environment Considering a global environment where the partners interchange their processes beyond the company boundaries, a web-based infrastructure is the most preferred platform Considering this, Workflow processes and e-Business structures were combined together on the web environment.

• 한국경영과학회지
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• 제20권3호
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• pp.1-16
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• 1995

Group collaborative systems are recently emerging to support a group of users engaged in common tasks such as group decision making, engineering design, group scheduling, or collaborative writing. This paper provides an change management framework for the group collaborative system to facilitate managing dependency relationship between shared objects and dependent user views, and coordinating change and propagation activities between the two in distributed computing environments. Specifically, the framework adopts an object-oriented database paradigm and presents several object constructs capturing dependency management and change notification mechanisms. First, it introduces change management mechanisms with transient shared objects and secondly, it extends them into presistent object computing environment by integrating transaction management mechanisms and change notification mechanisms. A prototype change management framework is developed on a commercial object-oriented database management system.