• Journal of Integrative Natural Science
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• v.14 no.4
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• pp.183-188
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• 2021

Collaborative filtering is one of the commonly used methods in the web recommendation system. Numerous researches on the collaborative filtering proposed the numbers of measures for enhancing the accuracy. This study suggests the movie recommendation system applied with Word2Vec and ensemble convolutional neural networks. First, user sentences and movie sentences are made from the user, movie, and rating information. Then, the user sentences and movie sentences are input into Word2Vec to figure out the user vector and movie vector. The user vector is input on the user convolutional model while the movie vector is input on the movie convolutional model. These user and movie convolutional models are connected to the fully-connected neural network model. Ultimately, the output layer of the fully-connected neural network model outputs the forecasts for user, movie, and rating. The test result showed that the system proposed in this study showed higher accuracy than the conventional cooperative filtering system and Word2Vec and deep neural network-based system suggested in the similar researches. The Word2Vec and deep neural network-based recommendation system is expected to help in enhancing the satisfaction while considering about the characteristics of users.

• Journal of The Korean Association of Information Education
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• v.24 no.4
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• pp.401-412
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• 2020

Team-based programming methods are widely applied to solve various difficulties that pre-service teachers experience in the programming lessons. To prepare effective collaboration strategies necessary for them, it is necessary to analyze various collaborative factors that affect learners' programming competencies. Therefore, in this article, a questionnaire survey was conducted by dividing learners' collaboration factors into individual and team competencies, and the relationship between learners' programming competencies was analyzed. As a result of the verification, the program design competency showed significant results in all elements of the learner's personal competency, team techniques such as data sharing skills necessary for collaboration, and team collaboration. It was analyzed that an individual's understanding of learning and team collaboration influenced the program implementation competency. In addition, the group with relatively high team technique showed significant differences in programming competence, interest, and satisfaction. Accordingly, by linking meaningful factors related to individual and team competencies according to the programming process, a collaborative strategy practically necessary for pre-service teachers was suggested.

• Journal of Korea Society of Digital Industry and Information Management
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• v.6 no.3
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• pp.191-201
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• 2010

The Korean central government has been investing a lot of efforts to promote performance of local governments. For example, the Ministry of Public Administration and Security (MOPAS) supported the local governments to develop and provide with a 'balanced score card' and a 'customer satisfaction innovation. ' Many other central ministries also conducted individual evaluations for local governments in their substantive policy areas. These evaluation systems of 78 appraisals for local governments conducted by the MOPAS and other ministries had made the local governments to work harder. However, most local governments have appealed their 'reform fatigue' caused by the overlapping evaluation systems. In this context, the MOPAS initiated merging the evaluations into a co-evaluation system under the new Government Performance Evaluation Act of 2006. In this process of introduction of new evaluation system, there are two significant movements. Firstly, as Korean Government has strong information technology, MOPAS has developed 'Virtual Policy Studio (VPS)' which evaluates the performance of each local government with on line. In other words, in the co-evaluation system for local government performance most evaluation steps are implemented by computer and Internet. So most stakeholder can access and work on the VPS in real time when they want to. And the other thing is that cooperation among stakeholders has been occurred in the co-evaluation system. Furthurmore the cooperative governance is systemized and sustain for a long time because MOPAS made IT based co-evaluation system. Therefore this paper intends to illustrate the process of introduction of VPS, main process of co-evaluation system based on VPS and analyze collaborative governance of the co-evaluation system.

• The Journal of the Korea Contents Association
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• v.7 no.4
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• pp.66-73
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• 2007

Internet is a part of our common life and tremendous information is cumulated. In these trends, the personalization becomes a very important technology which could find exact information to present users. Previous personalized services use content based filtering which is able to recommend by analyzing the content and collaborative filtering which is able to recommend contents according to preference of users group. But, collaborative filtering needs the evaluation of some amount of data. Also, It cannot reflect all data of users because it recommends items based on data of some users who have similar inclination. Therefore, we need a new recommendation method which can recommend prefer items without preference data of users. In this paper, we proposed the apparel coordination system using personalized preference on the semantic web. This paper provides the results which this system can reduce the searching time and advance the customer satisfaction measurement according to user's feedback to system.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.2
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• pp.112-123
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• 2005

The latest E-commerce sites provide personalized services to maximize user satisfaction for Internet user The collaborative filtering is an algorithm for personalized item real-time recommendation. Various supplementary methods are provided for improving the accuracy of prediction and performance. It is important to consider these two things simultaneously to implement a useful recommendation system. However, established studies on collaborative filtering technique deal only with the matter of accuracy improvement and overlook the matter of performance. This study considers representative attribute-neighborhood, recommendation textile set, and similarity grouping that are expected to improve performance to the recommendation agent system. Ultimately, this paper suggests empirical applications to verify the adequacy and the validity on this system with the development of Fashion Design Recommendation Agent System (FDRAS ).

• Journal of the Korea Convergence Society
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• v.11 no.8
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• pp.23-31
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• 2020

The need for personalized recommendation is growing due to convenient access and various types of items due to the development of information communication and smartphones. Weather and weather conditions have a great influence on the decision-making of users' places and activities. This weather information can increase users' satisfaction with recommendations. In this paper, we propose a collaborative filtering-based place recommendation system using living index by utilizing living index of users' location information on mobile platform to find users with similar propensity and to recommend places by predicting preferences for places. The proposed system consists of a weather module for analyzing and classifying users' weather, a recommendation module using collaborative filtering for place recommendations, and a management module for user preferences and post-management. Experiments have shown that the proposed system is valid in terms of the convergence of collaborative filtering algorithms and living indices and reflecting individual propensity.

• Journal of Information Management
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• v.41 no.4
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• pp.227-249
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• 2010

Scholarly information has increased tremendously according to the development of IT, especially the Internet. However, simultaneously, people have to spend more time and exert more effort because of information overload. There have been many research efforts in the field of expert systems, data mining, and information retrieval, concerning a system that recommends user-expected information items through presumption. Recently, the hybrid system combining a content-based recommendation system and collaborative filtering or combining recommendation systems in other domains has been developed. In this paper we resolved the problem of the current recommendation system and suggested a new system combining collaborative filtering and Naive Bayes Classification. In this way, we resolved the over-specialization problem through collaborative filtering and lack of assessment information or recommendation of new contents through Naive Bayes Classification. For verification, we applied the new model in NDSL's paper service of KISTI, especially papers from journals about Sitology and Electronics, and witnessed high satisfaction from 4 experimental participants.

• Journal of Digital Convergence
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• v.16 no.9
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• pp.91-98
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• 2018

This study was conducted to verify the mediating effect of knowledge sharing activity on the effect of trust between consultants on consulting satisfaction during consulting collaboration process. Regression analysis was performed using SPSS 23 based on the survey data. The results showed that trust between consultants had significant effects on knowledge sharing and on consulting satisfaction. Knowledge sharing activities partially mediated the effects of trust between consultants on consulting satisfaction. Further research is required to find out the various factors that are needed to further enhance competence and knowledge sharing for consultants in order to facilitate collaborative work in a rapid change of management environment.

• Journal of Digital Contents Society
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• v.19 no.5
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• pp.935-944
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• 2018

The purpose of this study is to investigate the impact of Airline Partner Organization members ' perception of supply chain management characteristics on the satisfaction of the relationship and to verify the parameter effectiveness of collaboration. An empirical study was conducted through survey techniques to achieve the objectives of the study. Research has shown that the factors for building trust, immersion, and sharing of vision tables, other than information sharing, are significant prerequisites for collaboration. We have identified statistically significant effects of collaborative factor on relationship satisfaction factor. Additionally, it was confirmed that there was a parameter effect between supply chain management characteristics recognition and relationship satisfaction by testing the effectiveness of the collaboration.

• Journal of Intelligence and Information Systems
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• v.7 no.1
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• pp.149-159
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• 2001

There have been lots of researches for providing a personalized service to a customer using one-to-one marketing and collaborative filtering techniques in E-Commerce. However, there are technical difficulties for providing the recommendation of products far users, which often involve high complexity of computation. In this paper, we have presented an integrated method of classification problem solving method and constraint based configuration techniques. This method can reduce a complexity of computation by classifying a solution domain space that has a higher complexity of composition. Thereafter, we have modeled customers constraints and the components of products to configure a complete system by passing it to constraint processing module in Constraint Satisfaction Problems. Constraint-based configuration uses the constraint propagation using the constraints of buyers and the constraints among PC components to configure a proper product for a customer. We have transformed and applied vector space modeling method in the field of information retrieval to consider a customer satisfaction in addition to the CSP. Finally, we have applied our system to test data fur evaluating a customers satisfaction and performance of the proposed system.