• 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 Korea Institute of Information and Communication Engineering
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• v.16 no.12
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• pp.2657-2664
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• 2012

Web-based learning receives much attention as an effective learning method because users can use the learning service at any time from any space. A learning management system(LMS) provides online educational environment among teachers and students, supporting various facilities to deliver educational contents. Since most of the existing LMSs support one-way or limited two-way teaching services among teachers and students, there are a lot of difficulties in performing collaboration among students and/or collaboration among teachers and students. In this paper, we describe the development of collaborative workspaces which provides effective collaborative educational environment on Moodle which is widely accepted as a typical LMS. Through the provided various types of collaborative workspaces, users can easily perform group activities, sharing educational with appropriate access control mechanism.

• Journal of Information Technology Applications and Management
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• v.12 no.3
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• pp.41-56
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• 2005

Product recommender system is one of the most popular techniques for customer relationship management. In addition, collaborative filtering (CF) has been known to be one of the most successful recommendation techniques in product recommender systems. However, CF has some limitations such as sparsity and scalability problems. This study proposes hybrid cluster analysis and case-based reasoning (CBR) to address these problems. CBR may relieve the sparsity problem because it recommends products using customer profile and transaction data, but it may still give rise to scalability problem. Thus, this study uses cluster analysis to reduce search space prior to CBR for scalability Problem. For cluster analysis, this study employs hybrid genetic and K-Means algorithms to avoid possibility of convergence in local minima of typical cluster analyses. This study also develops a Web-based prototype system to test the superiority of the proposed model.

• Research in Mathematical Education
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• v.15 no.1
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• pp.15-30
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• 2011

We study to design educational Logo-based microworld environment equipped with 3D construction capability, 3D manipulation, and web-based communication. Extending the turtle metaphor of 2D Logo, we design simple and intuitive symbolic representation system that can create several turtle objects and operations. We also present various mathematization activities applying the turtle objects and suggest the way to make good use of them in mathematics education. In our microworld environment, the symbolic representations constructing the turtle objects can be used for web-based collaborative learning, communication, and assessments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.12
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• pp.2601-2608
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• 2010

It is difficult to merge text document and to remake use of documents on the most collaborative document authoring system using text document, and also to provide the storage place for saving and keeping documents. It has vulnerable drawbacks about the security though it provides the accessible abilities due to basing it on Web. In this paper, we design and implementation the collaborative document authoring system for XML document to improve a couple of problems on these systems. For these, we based on the DOM to manipulate the modeling object documents and utilized RMI on this system without considering socket communication when it transmits and receives Java objects. We improved the security through processes of authentication. By providing templates and editing functions such as annotation, visualization of document structures, we made easier making collaborative document authoring more than ever.

• Journal of Intelligence and Information Systems
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• v.8 no.2
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• pp.91-103
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• 2002

A collaborative filtering which supports personalized services of users has been common use in existing web sites for increasing the satisfaction of users. A collaborative filtering is demanded that items are estimated more than specified number. Besides, it tends to ignore information of other users as recommending them on the basis of information of partial users who have similar inclination. However, there are valuable hidden information into other users' one. In this paper, we use Association Rule, which is common wide use in Data Mining, with collaborative filtering for the purpose of discovering those information. In addition, this paper proved that Association Rule applied to Recommender System has a effects to recommend users by the relation between groups. In other words, Association Rule based on the history of all users is derived from. and the efficiency of Recommender System is improved by using Association Rule with collaborative filtering.

• The Journal of Korean Institute for Practical Engineering Education
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• v.2 no.1
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• pp.64-70
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• 2010

The purpose of this study is to understand students' use intentions of Web Based Collaborative Learning (WBCL) system. To meet this purpose, we developed a research model based on the Decomposed TPB. This model contains 5 influencing factors: Explicit social influence(EXSI) and Implicit social influence(IMSI), Perceived Usefulness (PU), Perceived easy of use(PEOU), Perceived Playfulness(PP). Data was collected 254 university students from two different institutions. Also, the analysis is conducted to do the hypothesis testing by using PLS 3.0. The result shows that influence factors except PEOU have a important and significant impact on user Behavior Intention(BI). Using WBCL system and learning tool, team leader(that is referent) and members can be a good interaction. For these same reasons, We found that especialy Explicit social influence(EXSI) and Implicit social influence(IMSI) are special influence factors in reference group.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.6
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• pp.663-669
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• 2004

A nuclear power plant is composed of a number of primary components. Maintaining the integrity of these components is one of the most critical issues in nuclear industry. In order to maintain the integrity of these primary components, a complicated procedure is required including regular in-service inspection, failure assessment, fracture mechanics analysis, etc. Also, experts in different fields have to co-operate to resolve the integrity issues on the basis of inspection results. This integrity evaluation process usually takes long, and thus, is detrimental for the plant productivity. Therefore, an effective safety evaluation system is essential to manage the integrity issues on a nuclear power plant. In this paper, a web-based fatigue life evaluation system for primary components in nuclear power plant is proposed. This system provides engineering knowledge-based information and concurrent and collaborative working environment through internet, and thus, is expected to raise the efficiency of integrity evaluation procedures on primary components of a nuclear power plant.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.05a
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• pp.342-351
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• 2002

A personalized product recommendation is an enabling mechanism to overcome information overload occurred when shopping in an Internet marketplace. Collaborative filtering has been known to be one of the most successful recommendation methods, but its application to e-commerce has exposed well-known limitations such as sparsity and scalability, which would lead to poor recommendations. This paper suggests a personalized recommendation methodology by which we are able to get further effectiveness and quality of recommendations when applied to an Internet shopping mall. The suggested methodology is based on a variety of data mining techniques such as web usage mining, decision tree induction, association rule mining and the product taxonomy. For the evaluation of the methodology, we implement a recommender system using intelligent agent and data warehousing technologies.

• Journal of Digital Contents Society
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• v.16 no.1
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• pp.79-83
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• 2015

This paper suggested a cyber collaboration platform based on web for food safety service. We implemented the cyber collaboration platform for food safety service so that the users participated in collaborative work may refer shared media objects as the same view to others. In this paper, we discussed a model for increasing reliability of food safety data through N screen server and client model. This paper explained a performance analysis of a system with function comparison running on multimedia collaboration work based on web and N screen techniques.