• Journal of Intelligence and Information Systems
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• v.9 no.1
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• pp.211-225
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• 2003

This paper aims at the design of collaborative architecture for business to business (B2B) applications based on Web service protocol. As different business processes should be interfaced in the B2B environment collaboration is important fur the success of B2B implementation. For the development tools, XML, Web services and ASP.NET were adopted Web services are emerging to provide a systematic and extensible framework for application-to-application interaction. The Web services framework is divided into three areas; communication protocols, service descriptions and Web discovery. Web services such as SOAP, WSDL and UDDI correspond to the three areas respectively. ASP.NET is utilized which corresponds to the component and service set located in the top layer of .NET. For the service of product category and product details, Web service architecture was implemented based upon the SQL server database.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.631-637
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• 2014

Recently, SNS is widely used for various purposes such as fast decision making or effective business process in educational institutions or enterprise as well as general services for social networking. Unfortunately, all of existing general SNS platforms do not provide user groups with workspaces for sharing information in a hierarchical way, nor support the functionality of workspace backup for migrations. In this paper, we present a collaborative workspace environment named ElggSpace which extends the Elgg SNS platform with the C3ware collaborative middleware. With the help of C3ware, ElggSpace systematically supports collaborative workspaces that enable user groups to share massive resource in cloud storages. In addition, ElggSpace allows high-level access controls for resources management and the functionality of resource backup, supporting effective collaboration.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.8
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• pp.970-977
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• 2020

The collaborative filtering recommendation technique has been the most widely used since the beginning of e-commerce companies introducing the recommendation system. As the online purchase of products or contents became an ordinary thing, however, recommendation simply applying purchasers' ratings led to the problem of low accuracy in recommendation. To improve the accuracy of recommendation, in this paper suggests the method of collaborative filtering that analyses product reviews and uses them as a weighted value. The proposed method refines product reviews with text mining to extract features and conducts sentiment analysis to draw a sentiment score. In order to recommend better items to user, sentiment weight is used to calculate the predicted values. The experiment results show that higher accuracy can be gained in the proposed method than the traditional collaborative filtering.

• Journal of information and communication convergence engineering
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• v.13 no.2
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• pp.86-96
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• 2015

In mobile communication, mobile services [MSs] (e.g., phone calls, short/multimedia messages, and Internet data) incur a cost to both mobile users (MUs) and mobile service providers (MSPs). The proposed model MobPrice consists of dynamic data pricing schemes for mobile communication in order to achieve optimal usage of MSs at minimal prices. MobPrice inspires MUs to subscribe MSs with flexibility of data sharing and intra-peer exchanges, thereby reducing overall cost. The main contributions of MobPrice are three-fold. First, it proposes a novel k-level data-pricing (kDP) scheme for MSs. Second, it extends the kDP scheme with the notion of service-sharing-based pricing schemes to a collaborative peer-to-peer data-pricing (pDP) scheme and a cluster-based data-pricing (cDP) scheme to incorporate the notion of 'cluster' (made up of two or more MUs) in mobile communication. Third, our performance study shows that the proposed schemes are indeed effective in maximizing MS subscriptions and minimizing MS's price/user.

• Journal of Information Processing Systems
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• v.18 no.3
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• pp.389-401
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• 2022

The business of Internet of Vehicles (IoV) is growing rapidly, and the large amount of data exchange has caused problems of large mobile network communication delay and large energy loss. A strategy for resource allocation of IoV communication based on mobile edge computing (MEC) is thus proposed. First, a model of the cloud-side collaborative cache and resource allocation system for the IoV is designed. Vehicles can offload tasks to MEC servers or neighboring vehicles for communication. Then, the communication model and the calculation model of IoV system are comprehensively analyzed. The optimization objective of minimizing delay and energy consumption is constructed. Finally, the on-board computing task is coded, and the optimization problem is transformed into a knapsack problem. The optimal resource allocation strategy is obtained through genetic algorithm. The simulation results based on the MATLAB platform show that: The proposed strategy offloads tasks to the MEC server or neighboring vehicles, making full use of system resources. In different situations, the energy consumption does not exceed 300 J and 180 J, with an average delay of 210 ms, effectively reducing system overhead and improving response speed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.191-199
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• 2015

The purposes of this study are to examine the predictability of variables related to SNS intention to use in collaborative learning and provide some new implications. Based on Technology Readiness and Acceptance Model (TRAM), we hypothesized that optimism, innovativeness, discomfort, insecurity as personal disposition variables, subjective norm as a social variable, and perceived usefulness and perceived ease of use as cognitive variables would predict SNS intention to use. For this study, 274 'Share Leadership' students in E university completed surveys and it was analyzed by multiple regression analysis. The results of this study showed as follows. First, optimism, innovativeness, discomfort, and subjective norm predicted perceived ease of use. Second, optimism, insecurity, subjective norm and perceived ease of use predicted perceived usefulness. Third, subjective norm, perceived ease of use and perceived usefulness predicted SNS intention to use. From this, it is revealed that positive technology readiness predict much more than negative technology readiness do and the role of teacher and peers is very important.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.4 no.4
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• pp.767-773
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• 2000

As computer systems and communication technologies develop rapidly, CSCW(Computer Supported Collaborative Work) system appears nowadays, through which it is available to work on virtual space without any restriction of time and place. Most of CWCS systems depend on a special network and groupware. The systems of graphics and CAD are not so many because they are specified by hardware and application software. In this paper, we propose a web-based collaborative CAD system, which can be jointly worked on Internet WWW being independent from any platforms. It can create and modify 3D objects easily using VRML and Java 3D API, and it can send, print, and store them. The interactive work for designing objects can be also carried out through chatting with each other. This system is executed in the environment of Client/server architecture. Clients connect to the CAD sewer through Java applet on WWW. The server is implemented by Java application, and it consists of three components : connection manager which controls the contact to users, work manager which keeps viewing in concurrency and provides virtual work space sharing with others, and solid modeler which creates 3D object.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.221-226
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• 2021

Collaborative filtering based recommender systems recommend user-preferrable items based on rating history and are essential function for the current various commercial purposes. In order to determine items to recommend, prediction of preference score for unrated items is estimated based on similar rating history. Previous studies usually employ two methods individually, i.e., similar user based or similar item based ones. These methods have drawbacks of degrading prediction accuracy in case of sparse user ratings data or when having difficulty with finding similar users or items. This study suggests a new rating prediction method by integrating the two previous methods. The proposed method has the advantage of consulting more similar ratings, thus improving the recommendation quality. The experimental results reveal that our method significantly improve the performance of previous methods, in terms of prediction accuracy, relevance level of recommended items, and that of recommended item ranks with a sparse dataset. With a rather dense dataset, it outperforms the previous methods in terms of prediction accuracy and shows comparable results in other metrics.

• Journal of Mechanical Science and Technology
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• v.20 no.1
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• pp.133-146
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• 2006

Collaborative optimization (CO) is a multi-level decomposed methodology for a large-scale multidisciplinary design optimization (MDO). CO is known to have computational and organizational advantages. Its decomposed architecture removes a necessity of direct communication among disciplines, guaranteeing their autonomy. However, CO has several problems at convergence characteristics and computation time. In this study, such features are discussed and some suggestions are made to improve the performance of CO. Only for the system level optimization, genetic algorithm is used and gradient-based method is used for subspace optimizers. Moreover, response surface models are replaced as analyses in subspaces. In this manner, CO is applied to aero-structural design problems of the aircraft wing and its results are compared with the multidisciplinary feasible (MDF) method and the original CO. Through these results, it is verified that the suggested approach improves convergence characteristics and offers a proper solution.

• Korean Journal of Computational Design and Engineering
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• v.9 no.4
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• pp.325-333
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• 2004

To ensure competitiveness in the modern automotive market, material arrangements and information managements should be performed concurrently with new car developments. In automotive general assembly shops, thus, new business workflow and supporting environments are inevitable to reduce the manufacturing preparation time in developing a new car in the manner of concurrent and collaborative engineering. Since complete material arrangements for a whole general assembly system is a huge and complex job, several planners should execute their planning jobs and share information. Therefore, each planner should provide others with his/her results with continuous on-line communication and cooperation. Digital automotive general assembly factory is useful the performing concurrent and collaborative engineering and is essential for material arrangements and information managements systems. In this research, we constructed a sophisticated digital factory of an automotive general assembly shop by measuring and modeling through the parametric 3-D CAD, and a web-based system for concurrent and collaborative material arrangements for automotive general assembly via 3D mock-up is developed. By the digital general assembly shop and developed web-based system, savings in time and colt of manufacturing preparation activities are possible, and the reliability of the planning result Is greatly improved.