• Korean Journal of Construction Engineering and Management
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• v.3 no.2 s.10
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• pp.87-98
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• 2002

Korea government is making an effort to improve the efficiency in construction industry by introducing CITIS (Contractor integrated Technical Information Service). In order to provide a base for the application of CITIS into the construction industry, this research provides a concept of virtual factory which should be incorporated into CITIS system for the successful collaborative work in the virtual space. It then implements a prototype system through process and data modeling to apply into the road construction projects. The prototype system is tested to verify its efficiency. Finally, lesson learned from these works is provided to advance the current CITIS toward a collaborative virtual factory.

• Journal of the Korea Society of Computer and Information
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• v.24 no.3
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• pp.95-104
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• 2019

Crowdsourcing is growing its interests in designing where various designers work independently to a given design task. Recent researchers discovered that collaboration by sharing designs among designers helps to produce high-quality designs. However, design task may still be hard even with that collaboration in case the requirements are not well-defined. Most customers sometimes do not know what they really want and do not know how to clearly define the requirements. Consequently, the lack of requirements creates issues on designers, such as spending much time and effort on collecting requirements alone or from the customers. The designers even end up missing important necessities to complete their tasks. To address this issue, we proposed a collaborative requirements elicitation method that supports designers who are working on the same task. We developed CREFD (Collaborative Requirements Elicitation For Designers and Developers) tool to enable designers collaboratively provide requirements, identify dependencies, add annotations and votes to the provided requirements. We performed the hypothetical and empirical evaluations to test and compare the proposed method with one of the existing elicitation methods, the results show that the proposed method helps in collecting accepted and well-organized requirements better than individual requirements elicitation.

• Journal of the Korean Institute of Educational Facilities
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• v.26 no.3
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• pp.33-41
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• 2019

As the information age matures, the learning style of youth is changing rapidly. Students study at a variety of places such as cafe or lobbies utilizing various digital learning devices. Along with the place changes, learning methods are also changing. Student-centered learning methods such as smart learning, collaborative learning, and activity-based learning are increasingly being utilized instead of the traditional instructor-centered learning in which knowledge is unilaterally delivered. Accordingly, many universities are remodeling central libraries, and they are also transforming lobby spaces of the college buildings into simple but useful learning spaces. In this study, we analyze the characteristics of learning spaces in universities from the standpoint of the students. According to the analysis, overall satisfaction is high in terms of comfortable physical learning environments such as Wi-Fi, furniture, lighting, etc. But the spaces are still optimized for individual and intensive learning. There seems to be a lack of effort to support collaborative learning or activity-based learning. This observation is confirmed by the characteristics of the central library, and it is considered that the reason why the college buildings are preferred by students is that college buildings are more suitable for collaborative or activity-based learning than libraries.

• Journal of the Korea Society of Computer and Information
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• v.23 no.8
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• pp.45-50
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• 2018

Many of the current successful commercial recommender systems utilize collaborative filtering techniques. This technique recommends products to the active user based on product preference history of the neighbor users. Those users with similar preferences to the active user are typically named his/her neighbors. Hence, finding neighbors is critical to performance of the system. Although much effort for developing similarity measures has been devoted in the literature, there leaves a lot to be improved, especially in the aspect of handling subjectivity or vagueness in user preference ratings. This paper addresses this problem and presents a novel similarity measure using fuzzy logic for selecting neighbors. Experimental studies are conducted to reveal that the proposed measure achieved significant performance improvement.

• Genomics & Informatics
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• v.7 no.1
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• pp.46-48
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• 2009

Finishing is the most time-consuming step in sequencing, and many genome projects are left unfinished due to complex repeat regions. Here, we have developed BACContigEditor, a prototype shotgun sequence finishing tool. It is essentially an editor that visualizes assemblies of shotgun sequence fragment reads as gapped multiple alignments. The program offers some flexibility that is needed to rapidly resolve complex regions within a working session. The sole purpose of the release is to promote collaborative creation of extensible software for fragment assembly editors, foster collaborative development, and reduce barriers to initial tool development effort. We describe our software architecture and identify current challenges. The program is available under an Open Source license.

• Asia pacific journal of information systems
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• v.15 no.3
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• pp.223-241
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• 2005

In spite of the rapid growth of mobile multimedia contents market, most of the customers experience inconvenience, lengthy search processes and frustration in searching for the specific multimedia contents they want. These difficulties are attributable to the current mobile Internet service method based on inefficient sequential search. To overcome these difficulties, this paper proposes a MOBIIe COntents Recommender System for Movie(MOBICORS-Movie), which is designed to reduce customers' search efforts in finding desired movies on the mobile Internet. MOBICORS-Movie consists of three agents: CF(Collaborative Filtering), CBIR(Content-Based Information Retrieval) and RF(Relevance Feedback). These agents collaborate each other to support a customer in finding a desired movie by generating personalized recommendations of movies. To verify the performance of MOBICORS-Movie, the simulation-based experiments were conducted. The results from this experiments show that MOBICORS-Movie significantly reduces the customer's search effort and can be a realistic solution for movie recommendation in the mobile Internet environment.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2001.10a
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• pp.25-28
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• 2001

Today enterprises are bringing forward the strong needs for the Global Work Space that is able to realize the collaboration of the virtual enterprise in order to achieve the rapid entrance to market, the quality improvement as well as the cost reduction of their new products. Especially, they are building the efficient Product Management Infrastructure in parallel with the real-time knowledge management for the information generated in the course of a product lifecycle and the Process Innovation making the Concurrent Engineering possible. Building a system in the web environment cannot be the entire effort to realize the Global Work Space within an enterprise that is an essential factor for the reduction of a product development period which in turn contributes to Time to Market. Various work models and processes are found in enterprises and many different application programs are developed and utilized to support these. This study proposes a scheme for the optimized Collaborative Workflow System Architecture that is able to take in and apply various application programs accompanied by the product development work process. Through this, we are to examine various limits and problems existing in the real-time collaborative system between enterprises and to reform these.

• Journal of Information Technology Services
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• v.7 no.3
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• pp.71-85
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• 2008

The rapid growth of blog has caused information overload where bloggers in the virtual community space are no longer able to effectively choose the blogs they are exposed to. Recommender systems have been widely advocated as a way of coping with the problem of information overload in e-business environment. Collaborative Filtering (CF) is the most successful recommendation method to date and used in many of the recommender systems. In this research, we propose a CF-based recommender system for bloggers to find their similar bloggers or preferable virtual community without burdensome search effort. For such a purpose, we apply the "Interest Value" to CF recommender systems. The Interest Value is the quantity value about users' transaction data in virtual community, and can measure the opinion of users accurately. Based on the Interest Value, the neighborhood group is generated, and virtual community list is recommended using the Community Likeness Score (ClS). Our experimental results upon real data of Korean Blog site show that the methodology is capable of dealing with the information overload issue in virtual community space. And Interest Value is proved to have the potential to meet the challenge of recommendation methodologies in virtual community space.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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• pp.267-269
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• 2019

There are many recommendation systems offer an effort to get better preciseness the information to the users. In order to further improve more accuracy, the social network analysis method which is used to analyze data to community detection in social networks was introduced in the recommendation system and the result shows this method is improving more accuracy. In this paper, we propose a movie recommendation system using social network analysis and normalized discounted cumulative gain with the best accuracy. To estimate the performance, the collaborative filtering using the k nearest neighbor method, the social network analysis with collaborative filtering method and the proposed method are used to evaluate the MovieLens data. The performance outputs show that the proposed method get better the accuracy of the movie recommendation system than any other methods used in this experiment.

• Journal of KIISE:Software and Applications
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• v.31 no.8
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• pp.1054-1061
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• 2004

At recent, people can easily access to information by Internet to be rapidly evolving. And also, the amount is rapidly increasing. So the techniques, to automatically extract the required information are very important to reduce the time and the effort for retrieving information. In this paper, we describe a collaborative filtering system for automatically recommending high-quality information to users with similar interests on arbitrarily narrow information domains. It asks a user to rate a gauge set of items. It then evaluates the user's rates and suggests a recommendation set of items. We interpret the process of evaluation as an inference mechanism that maps a gauge set to a recommendation set. We accomplish the mapping with FAM (Fuzzy Associative Memory). We implemented the suggested system in a Web server and tested its performance in the domain of retrieval of technical papers, especially in the field of information technologies. The experimental results show that it may provide reliable recommendations.