• Journal of the Korea Society of Computer and Information
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• v.21 no.7
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• pp.9-16
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• 2016

Collaborative filtering(CF) uses the purchase or item rating history of other users, but does not need additional properties or attributes of users and items. Hence CF is known th be the most successful recommendation technology. But conventional CF approach has some significant weakness, such as the new user problem. In this paper, we propose a approach using word embedding with skip-gram for learning distributed item representations. In particular, we show that this approach can be used to capture precise item for solving the "new user problem." The proposed approach has been tested on the Movielens databases. We compare the performance of the user based CF, item based CF and our approach by observing the change of recommendation results according to the different number of item rating information. The experimental results shows the improvement in our approach in measuring the precision applied to new user problem situations.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.914-915
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• 2017

Importance and usage of the recommender system increases with the increase of information. The accuracy of the system recommendation primarily depends on the data. There is a problem in recommender systems, known as cold start problem. The lack of data about new products and users causes the cold start problem, and the system will not be able to give correct recommendation. This paper deals with cold start problem by comparing product specification and the review of the resembled products. The user, who likes the resembled product of the new one has more probability of taking interest in the new product as well. However, if a user disagreed with resembled product due to some reasons which the user mentioned in the reviews. The new product overcomes that issue, so the user will greatly accept the new product. Therefore, the system needs to recommend new product to those users as well, in this way the cold start problem will get resolved.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.446-465
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• 2015

In this modern era of technology and information, e-learning approach has become an integral part of teaching and learning using modern technologies. There are different variations or classification of e-learning approaches. One of notable approaches is Personal Learning Environment (PLE). In a PLE system, the contents are presented to the user in a personalized manner (according to the user's needs and wants). The problem arises when a new user enters the system, and due to the lack of information about the new user's needs and wants, the system fails to recommend him/her the personalized e-learning contents accurately. This phenomenon is known as cold-start problem. In order to address this issue, existing researches propose different approaches for recommendation such as preference profile, user ratings and tagging recommendations. In this research paper, the implementation of a novel interaction-based approach is presented. The interaction-based approach improves the recommendation accuracy for the new-user cold-start problem by integrating preferences profile and tagging recommendation and utilizing the interaction among users and system. This research work takes leverage of the interaction of a new user with the PLE system and generates recommendation for the new user, both implicitly and explicitly, thus solving new-user cold-start problem. The result shows the improvement of 31.57% in Precision, 18.29% in Recall and 8.8% in F1-measure.

• Journal of the Korea Institute of Building Construction
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• v.4 no.2
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• pp.119-128
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• 2004

Lately construction industry tends to prefer remodeling of existing buildings rather than new construction or reconstruction of buildings due to strengthening of several restriction related to real estates along with prolonged depression. And also, remodeling of building costs less and creates less wastes compared to reconstruction and so it is more profitable in financial and environmental view. However remodeling is process of creating new environment with existing building. Therefor remodeling must follow the procedure realizing problem and fix the problem based on through investigation on existing building and users requirement must be faithfully reflected. Specially in case of apartment houses, since vagueness on ownership and management authority on common parts exists. Hereupon, in this study we are to present the procedure of analyzing apartment house remodeling method through user requirement by approaching to several considerable factors in user request side.

• Journal of Information Processing Systems
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• v.15 no.1
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• pp.127-136
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• 2019

User-based and item-based approaches have been developed as the solutions of the movie recommendation problem. However, the user-based approach is faced with the problem of sparsity, and the item-based approach is faced with the problem of not reflecting users' preferences. In order to solve these problems, there is a research on the combination of the two methods using the concept of similarity. In reality, it is not free from the problem of sparsity, since it has a lot of parameters to be calculated. In this study, we propose a combining method that simplifies the combination equation of prior study. This method is relatively free from the problem of sparsity, since it has less parameters to be calculated. Thus, it can get more accurate results by reflecting the users rating to calculate the parameters. It is very fast to predict new movie ratings as well. In experiments for the proposed method, the initial error is large, but the performance gets quickly stabilized after. In addition, it showed about 6% lower average error rate than the existing method using similarity.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.1
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• pp.99-104
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• 2014

Nowadays, various researches fulfill in many communication engineering area for B4G (Beyond Forth Generation). Next LTE-A (Long Term Evolution Advanced), MU-MIMO (Multi-User Multi Input Multi Output) method raises to upgrade throughput performance. However, the method of user selection is not decided because of many types and discussions in MU-MIMO system. Many existing methods are powerful for enhancing performance but have various restrictions in practical implementation. Fairness problem is primary restriction in this area. Existing papers emphasis algorithm to increase sum-rate but we introduce an algorithm about dealing with fairness problem for real commercialization implementation. Therefore, this paper introduces new user selection method in MU-MIMO system. This method overcomes a fairness problem in SUS (Semiorthogonal User Selection) algorithm. We can use the method to get a similar sum-rate with SUS and a high fairness performance. And this paper uses a hybrid method with SC-SUS (Superposition Coding SUS) algorithm and SUS algorithm. We find a threshold value of optimal performance by experimental method. We show this performance by computer simulation with MATLAB and analysis that results. And we compare the results with another paper's that different way to solve fairness problem.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.11a
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• pp.191-194
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• 2003

As internet commerce grows, many company has begun to use a CF (Collaborative Filtering) as a Recommender System. To achieve an accuracy of CF, we need to obtain sufficient account of voting scores from customers. Moreover, those scores may not be consistent. To overcome this problem, we propose a new recommendation scheme using binary user-item matrix, which represents whether a user purchases a product instead of using the voting scores. Through the experiment regarding this new scheme, a better accuracy is demonstrated.

• Journal of Korea Multimedia Society
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• v.22 no.4
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• pp.502-514
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• 2019

Existing user research methods are subject to a variety of research conditions such as the amount and variety of data collected and the expertise of the facilitator of a group research session. In this study, we propose a new user research methodology using an 'Issue-Network' system, which is developed based on the theory and methods of social network analysis. The Issue-Network is designed to define problem spaces from the issues raised by users in a group research session in a form of an interactive network graph. The system helps to break out of ordinary perspectives of looking into problem spaces by enabling an alternative and more creative way to connect issues in the network. In this study, we took a case study of generating the Issue-Network on behalf of the problems raised by users in various driving-related situations. We were able to draw three navigation usage scenarios that cover relatively important problem spaces: safety and being ready for the unexpected, smart navigation and notifications, making use of the spare time. In the future, the Issue-Network system is expected to be used as a tool to identify problems and derive solutions in group research sessions involving a large number of users.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2001.05a
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• pp.15-19
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• 2001

This paper describes effectiveness and characteristics of 3 P(point) task analysis as a new Ergonomic and Kansei design method for extracting user demand especially. The key point in 3 P task analysis is to describe the flow of tasks and extract any problems in each task. A solution of a problem means a user demand. 3 P task analysis cal eliminate an oversight of check items by examining the users' information processing level. The suers' information processing level was divided into the following three stages for problem extraction: acquirement of information ---> understanding and judgment ---> operation. Three stages has fourteenth cues such as difficulty of seeing, no emphasis, mapping for extracting problems. To link analysis results to the formulation of a product concept. I added a column on the right side of the table for writing the requirements (user demand) to resolve the problems extracted from each task. The requirements are extracted by using seventh cues. Finally 3 P task analysis was compared with group interview to make the characteristics of 3 P task analysis, especially extracting user demand, clear.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.3
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• pp.213-220
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• 2008

The object of this paper is to propose a method to deal with the problem of modeling user specifications in approaches based on supervisory control and Petri nets. However, most of Petri Net approaches are based on forbidden states specifications, and these specifications are suitable the use of tool such as the reachability graph. But these methods were not able to show the user specification easily and these formalisms are generally limited by the combinatorial explosion that occurs when attempting to model complex systems. Herein, we propose a new efficient method using FSSTP (Forbidden Sequences of State-Transitions Problem) and theory of region. Also, to detect and avoid the deadlock problem in control process, we use DAPN method (Deadlock Avoidance Petri nets) for solving this problem in control model.