• Management Science and Financial Engineering
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• v.12 no.2
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• pp.71-85
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• 2006

Collaborative filtering, among other recommender systems, has been known as the most successful recommendation technique. However, it requires the user-item rating data, which may not be easily available. As an alternative, some collaborative filtering algorithms have been developed recently by utilizing the market basket data in the form of the binary user-item matrix. Viewing the recommendation scheme as a two-class classification problem, we proposed a new collaborative filtering scheme using a regularized discriminant analysis applied to the binary user-item data. The proposed discriminant model was built in terms of the major principal components and was used for predicting the probability of purchasing a particular item by an active user. The proposed scheme was illustrated with two modified real data sets and its performance was compared with the existing user-based approach in terms of the recommendation precision.

• The Journal of Society for e-Business Studies
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• v.14 no.4
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• pp.47-57
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• 2009

Collaborative tagging systems allow users to attach tags to diverse sharable contents in social networks. These tags provide usefulness in reusing the contents for all community members as well as their creators. Three-dimensional data composed of users, items, and tags are used in the collaborative tag-based recommendation. They are generally more voluminous and sparse than two-dimensional data composed of users and items. Therefore, there are many difficulties in applying existing collaborative filtering methods directly to them. Latent factor models, which are also successful in the area of collaborative filtering recently, discover latent features(factors) for explaining observed values and solve problems based on the features. However, establishing the models require much time and efforts. In order to apply the latent factor models to three-dimensional collaborative filtering data, we have to overcome the difficulty of establishing them. This paper proposes various methods for determining preferences of users to items via establishing an intuitive model by assuming tags used for items as latent factors to users and items respectively. They are compared using real data for concluding desirable directions.

• Journal of The Korean Association of Information Education
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• v.22 no.1
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• pp.151-158
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• 2018

The purpose of this study is to develop a system for predicting students' collaborative problem solving ability based on the ICT factors of PISA 2015 that affect collaborative problem solving ability. The PISA 2015 computer-based collaborative problem-solving capability evaluation included 5,581 students in Korea. As a research method, correlation analysis was used to select meaningful variables. And the collaborative problem solving ability prediction model was created by using the deep learning method. As a result of the model generation, we were able to predict collaborative problem solving ability with about 95% accuracy for the test data set. Based on this model, a collaborative problem solving ability prediction system was designed and implemented. This research is expected to provide a new perspective on applying big data and artificial intelligence in decision making for ICT input and use in education.

• Agribusiness and Information Management
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• v.3 no.1
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• pp.1-10
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• 2011

In this exploratory analysis, we investigate the genesis and the evolution of local food-purchasing networks created and operated by consumers. In details, we describe how collecting and sharing information about food-products can become a central activity for some consumers' communities and how these communities are starting to play an active role in the food supply chain. We define this community-based food-purchasing model as collaborative food network (CFN), and we analytically describe its characteristics and differences with respect to the traditional and industrialized agrifood supply chain models. A collaborative food network community in Italy, known as GAS ("Gruppi di Acquisto Solidale" - "Solidarity Purchasing Groups"), is introduced as an example of our analytical model. We will use this empirical example to present the strengths and weaknesses of the CFN model.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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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.

• Journal of Information Technology Applications and Management
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• v.13 no.4
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• pp.197-214
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• 2006

This study explores factors to facilitate web-based collaborative learning and the effect of learning, based on the PBL(Problem Based Learning) from the constructivist approach in e-learning. A research model, using the key variables such as situations, interactions, and systems, was developed. In order to test this proposed model, experimental design and post-survey was conducted to the learners who took on-line and off-line course with team project. In the research model, situation category was divided into instructor's support, unstructured problem, and self-directed learning. Interaction category was divided into three factors; 'interaction between learners', 'interaction between learner and instructor', and 'interaction between learner and technology'. System category was divided into.monitoring and incentives. As a result, it was found that collaborative learning can be improved by situations, interactions, and systems, and the effectiveness of learning can be improved by situations and interactions in PBL.

• Journal of Internet Computing and Services
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• v.11 no.5
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• pp.95-104
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• 2010

As the computer and the communication technology are an unity, the collaborative learning based on constructivism is emphasized more than learning by forming external representation. Especially, online has characteristics not only to facilitate collaborative activities but to make students collaborators. In online collaborative learning, learning task is an integrated element in course design and an important portion deciding learning design, learning environment and learning process. Thus this study explored collaborative learning model according to the learning task type.

• Journal of Korean Society of Rural Planning
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• v.20 no.2
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• pp.23-43
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• 2014

This study aims to analyze the affecting factors-construction of collaborative planning process and effect on Comprehensive Rural Village Development Project. To this end, targeting the 36 districts which were selected for 2004 Comprehensive Rural Village Development Project and completed their 2010 5-year projects, components of collaborative planning process and planning effect will be drawn and the affecting factors-construction of collaborative planning and effect on Comprehensive Rural Village Development Project will be analyzed below. According to the results of this study, the affecting factors of collaborative planning process of Comprehensive Rural Village Development Project on planning effect, The level of effect of individual component on endogenous variable appeared greatest mostly in the upper groups. In terms of the level of individual component effect, social learning process and interaction among participants affected greatest. The process of Comprehensive Rural Village Development Project is evaluated that it reflected collaborative planning theory of Healey enough. Therefore, in the course of Comprehensive Rural Village Development Project progress, collaborative planning model must pass social learning process and interaction among participants which are the most important components out of collaborative planning process as we saw in the upper groups. And in order to maximize the performance and results of Comprehensive Rural Village Development Project, the following sequential affecting factors model as Figure 7 must be suggested as optimal collaborative planning models of Comprehensive Rural Village Development Project. Based on the results of the study, the policy implication was drawn as follows. First, systematic supplementations in the form of a consultative body are required to perform Comprehensive Rural Village Development Project efficiently. Second, network needs to be built among different participants in Comprehensive Rural Village Development Project process. Third, systematic mechanism is required to improve social learning among different participants. Fourth, systematic rearrangement is required to guarantee the residents' realistic participation in the course of Comprehensive Rural Village Development Project process.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.17
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• pp.7327-7331
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• 2014

Background: We had previously showed that the neutrophil lymphocyte ratio (NLR), ${\gamma}$-glutamyl transpeptidase (GGT) and carcinoembryonic antigen (CEA) are prognostic factors for metastatic colorectal cancer (mCRC) patients. In this study we developed a prognostic model based on these three indices. Materials and Methods: A total of 243 patients who were initially diagnosed as mCRC between 2005 and 2010 in the Sun Yat-sen University Cancer Center were studied. The endpoint was overall survival (OS). Results: NLR>3, elevated GGT and elevated CEA were confirmed as independent risk factors which could predict poor prognosis. Patients could be divided into three groups according to the number of risk factors they had. Those with two or three were defined as the high risk group, individuals with one risk factor as the modest risk group and patients without risk factor as the low risk group. The OS values for these three groups were 16.2 months (2.80~68.8), 24.2 months (4.07~79.0), and 37.2 months (12.6~87.8), respectively (p<0.001). Conclusions: We developed a simple but useful model based on NLR, GGT and CEA to provide prognostic information to clinical practice in highly selected mCRC patients. Further prospective and multi-center studies are warranted to test our model.

• Journal of the Korea Society of Computer and Information
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• v.21 no.3
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• pp.17-23
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• 2016

In this paper, we propose a model of the collaborative authoring tool and its implementation results. In the 'collaborative authoring and automatic distribution system,' users can create eBooks by using partial works (primary and edited sources) on the basis of copyright information registered by the primary author. The Collaborative Authoring Tool is a part of "the collaborative authoring and automatic distribution system" developed through research on "the development of key technologies of social work protection and content mashup tools" as an R&D project granted by the Korea Copyright Commission from 2013. In the collaborative authoring and automatic distribution system, authors of primary sources such as images, audio clips and video clips for eBooks can register them together with the copyright information; users can edit the primary sources to produce secondary sources and in turn register the secondary sources on the system; and users can create and distribute eBooks by using the sources registered in the system.