• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1997.06a
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• pp.75-81
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• 1997

A new DTPP (Desk-Top Program Production) system has been developed that enables multiple program producers (directors) working at different locations to collaborate over a computer network and prepare a single program for broadcasting. In this system, information is shared among users by exchanging data edited on non-linear editing terminals in program post-production work over a network in real time. In short, the new DTPP system provides a collaborative work space for producing TV programs. The system does not make use of a special server for collaborative work but rather multiple interconnected editing terminals having the same functions. In this configuration, data at a terminal which has just been edited by some operation is forwarded to all other connected terminals for updating. This form of information sharing, however, requires that some sort of data synchronizing method be established since multiple terminals are operating on the same data simultaneously. We therefore adopt a method whereby the system synchronizes the clocks on each terminal at the time of connection and sends an operation time stamp together with edited data. This enables most recently modified data to be identified and all information on all terminals to be updated appropriately. This paper provides an overview of this new collaborative DTPP system and describes the techniques for exchanging edited data and synchronizing data.

• Journal of Intelligence and Information Systems
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• v.14 no.2
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• pp.157-177
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• 2008

Even in a single day, an enormous amount of content including digital videos, posts, photographs, and wikis are generated on the web. It's getting more difficult to recommend to a user what he/she prefers among these contents because of the difficulty of automatically grasping of content's meanings. CF (Collaborative Filtering) is one of useful methods to recommend proper content to a user under these situations because the filtering process is only based on historical information about whether or not a target user has preferred an item before. Collaborative Tagging is the process that allows many users to annotate content with descriptive tags. Recommendation using tags can partially improve, such as the limitations of CF, the sparsity and cold-start problem. In this research, a CF method with user-created tags is proposed. Collaborative tagging is employed to grasp and filter users' preferences for items. Empirical demonstrations using real dataset from del.icio.us show that our algorithm obtains improved performance, compared with existing works.

• Korean Institute of Interior Design Journal
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• v.13 no.5
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• pp.223-229
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• 2004

The investment scale of design project has been increased rapidly following the recent social and economical demand. The demand of user has been changed variously together with social background like the increase of interest for the high level information oriented society and environment. In addition, it is necessary for the experts like coordinator, architect, color expert, and light designer to collaborate in the interior design process. The expertise diverse areas should be related closely and collaboratively for the smooth processing. It is necessary for the design environment to be changed in order to exchange the information effectively within the proposed period by the variety fields' experts. It is a collaborative design in the design studio that the multi-members collect the related data, suggest the idea, and discuss closely, which makes a decision for the new design concept and design plan in the fixed time. It is necessary to make a new kind of communication media concept in the design process, where the multi-members participate, and the collaborative design is processed in physically simultaneous space or in the far distance such as it is done above. In this paper, it is investigated for the communication for the design and creative behavior to explain the collaborative work in the process of design. The characteristics of collaborative design and demand design environment are summarized in the background of this kind of the creative behavior concept. Especially, the communication media for increasing the process effectiveness is explained and the concept for the development of web based collaborative design system is summarized.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.10 s.241
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• pp.1353-1360
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• 2005

Injection-molded products serve a wide range of applications in our modem lives and their significance is ever increasing. However, difficulty of communication among related companies under the present system results in increase of lead time and decrease of production efficiency. The objective of this paper is the development of a web-based draft verification system in mold design processes. Although several commercial CAD systems offer draft verification functions, those systems are very expensive and inadequate to perform collaborative works. For collaborative work under the distributed environment, the proposed system uses native file transforming of CAD data into optimal format by using the ACIS kernel and InterOp. Functions of draft verification modules are constructed over the ActiveX control using the visual C++ and OpenGL. Therefore, collaborators related to the development of a new product are able to verify the draft and undercut over the Internet without commercial CAD systems. The system helps to reduce production cost, errors and lead-time to the market. Performance of the system is confirmed through various case studies.

• Korean Journal of Computational Design and Engineering
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• v.7 no.1
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• pp.57-65
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• 2002

The purpose of this research is to develop a collaborative architectural design system. Design collaboration requires an extensive use of communication methods as well as the participation of various experts from different domains. Such facts address several issues when the Internet and digital media are able to create a completely new work environment. The building design process was studied, and possible modes of design collaboration were defined. A prototype system is being developed in accordance with the defined collaboration model. The system integrates a set of communication tools and web-based design media. Such media include a synchronous multi-user web CAD tool, a schematic 3D design tool, and a electronic whiteboard. A project database was designed in order to coordinate the project-wide communication which elaborates technologies such as web-based data access. In order to find out the effectiveness of the system, a usability test was performed both in quantitative and qualitative manner. The research will contribute to the development of world-wide design and construction collaboration through the Internet, which is becoming a mainstream building process model.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.286-291
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• 2008

Intelligence of collaborative environments starts from a trial to provide optimal services to with users based on real-time information about participants and environments of the collaboration itself. Up to now, we can collect information such as temperature, light, time, each participant's gestures, faces, voices, and locations by adopting ubiquitous computing technologies. However, since social relationship is intrinsic to collaborative activities, the relationships and roles among participants should be fully considered to provide optimal services. To do so, we have to integrate collected data from various sensors and extracted data about relationships and roles among participants as unified one context. Thus, this paper designs collaborative services filtered, by using the integrated data as a context, and introduces an implemented example, context-aware based interactive display service, called as smart meeting system (SMeet system).

• Journal of Intelligence and Information Systems
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• v.11 no.1
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• pp.107-121
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• 2005

Recently, many researches on recommendation systems and collaborative filtering have been proceeding in both research and practice. However, although product items may have multi-valued attributes, previous studies did not reflect the multi-valued attributes. To overcome this limitation, this paper proposes new methodology for recommendation system. The proposed methodology uses multi-valued attributes based on clustering technique for items and applies the collaborative filtering to provide accurate recommendations. In the proposed methodology, both user clustering-based CBR and item attribute clustering-based CBR technique have been applied to the collaborative filtering to consider correlation of item to item as well as correlation of user to user. By using multi-valued attribute-based clustering technique for items, characteristics of items are identified clearly. Extensive experiments have been performed with MovieLens data to validate the proposed methodology. The results of the experiment show that the proposed methodology outperforms the benchmarked methodologies: Case Based Reasoning Collaborative Filtering (CBR_CF) and User Clustering Case Based Reasoning Collaborative Filtering (UC_CBR_CF).

• Journal of Korea Multimedia Society
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• v.3 no.1
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• pp.63-76
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• 2000

Most work done in CSCW (Computer Supported Collaborative Work) system has been targeted toward supporting the exchange of documents or messages among group members, and yet support for cognitive aspects such as group organization, division and merge of work, and work flow control. The objective of the study is to provide CSCW environment for the engineering design process such as CAD (Computer Aided Design) and CASE (Computer Aided Software Engineering). The proposed DCWA (Distributed Collaborative Writing Aid) system suggests a mechanism that unifies the group organization, work division, and work flow control in the CAO, CASE, and software simulation tool. In particular, CAD relates the group and work partition by providing expressing the relation of drawing object (e.g., binding, attachment, and proportional scaling) which is owned by different members of group, and CASE combining with the simulation tool supports the flexibility of the work flow control. Simulating the prototype before manu-facturing a product can reduce time and cost in development.

• Journal of Korea Multimedia Society
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• v.11 no.9
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• pp.1213-1226
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• 2008

A recommender system supports people in making recommendations finding a set of people who are likely to provide good recommendations for a given person, or deriving recommendations from implicit behavior such as browsing activity, buying patterns, and time on task. We proposed new recommender system which combined SOM(Self-Organizing Map) neural networks with the Collaborative filtering which most recommender systems hat applied First, we segmented user groups according to demographic characteristics and then we trained the SOM with people's preferences as ito inputs. Finally we applied the classic collaborative filtering to the clustering with similarity in which an recommendation seeker belonged to, and therefore we didn't have to apply the collaborative filtering to the whose data set. Experiments were run for EachMovies data set. The results indicated that the predictive accuracy was increased in terms of MAE(Mean-Absolute-Error).

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.4
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• pp.65-73
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• 2007

This study devotes to compare the accuracy of Top-N recommendations of items transacted on the web site for customers with the accuracy of rank conformity of the real ratings with estimated ratings for customers preference about items generated from two types of collaborative filtering algorithms. One is Neighborhood Based Collaborative Filtering Algorithm(NBCFA) and the other is Correspondence Mean Algorithm(CMA). The result of this study shows the accuracy of Top-N recommendations and the rank conformity of real ratings with estimated ratings generated by CMA are better than that of NBCFA. It would be expected that the customer's satisfaction in Recommender System is more improved by using the prediction result from CMA than NBCFA, and then Using CMA in collaborative filtering recommender system is more efficient than using NBCFA.