• Proceedings of the Korea Inteligent Information System Society Conference
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• 2007.05a
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• pp.309-320
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• 2007

The data imbalance problem which can be uncounted in data mining classification problems typically means that there are more or less instances in a class than those in other classes. It causes low prediction accuracy of the minority class because classifiers tend to assign instances to major classes and ignore the minor class to reduce overall misclassification rate. In order to solve the data imbalance problem, there has been proposed a number of techniques based on resampling with replacement, adjusting decision thresholds, and adjusting the cost of the different classes. In this paper, we study the feasibility of the combination usage of the techniques previously proposed to deal with the data imbalance problem, and suggest a combination method using genetic algorithm to find the optimal combination ratio of the techniques. To improve the prediction accuracy of a minority class, we determine the combination ratio based on the F-value of the minority class as the fitness function of genetic algorithm. To compare the performance with those of single techniques and the matrix-style combination of random percentage, we performed experiments using four public datasets which has been generally used to compare the performance of methods for the data imbalance problem. From the results of experiments, we can find the usefulness of the proposed method.

• Journal of KIISE:Software and Applications
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• v.31 no.2
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• pp.153-163
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• 2004

Many recommender systems are based on Content-based Filtering and Social Filtering Both methods have their own advantages and disadvantages, and they complement each other rather than compete. So incorporating of both methods can make the better system and combination technique controls the quality of the entire recommender system. In this paper, we presented each user has his own tendency to decide which is the better recommendation for himself among the various recommendation results, and suggested the Personalized combination technique. To represent user tendency, we defined and used loyalty, diversity and pioneerity and showed by experiments that our combination technique is useful. This combination technique improved the average coverage 23% and for the ceiling 40%.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.715-717
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• 2004

This paper proposes a new reconstruction method of high-resolution facial image from a low-resolution facial image based on a recursive error back-projection of top-down machine learning. A face is represented by a linear combination of prototypes of shape and texture. With the shape and texture information about the pixels in a given low-resolution facial image, we can estimate optimal coefficients for a linear combination of prototypes of shape and those of texture by solving least square minimization. Then high-resolution facial image can be obtained by using the optimal coefficients for linear combination of the high-resolution prototypes, In addition to, a recursive error back-projection is applied to improve the accuracy of synthesized high-resolution facial image. The encouraging results of the proposed method show that our method can be used to improve the performance of the face recognition by applying our method to reconstruct high-resolution facial images from low-resolution one captured at a distance.

• 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.

• Management & Information Systems Review
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• v.27
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• pp.53-69
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• 2008

In this paper we analyse performance of value strategy and moving average method among the non-financial listed companies whose fiscal year ends at December in the Korean Stock Exchange between 1996 and 2005. And we analyse combination investment performance of value investment and moving average method. After the analysis objective enterprises divide with the value stock and the growth stock, in accordance with moving average method we divide ascending stock and descending stock. And we compose 6 portfolios with combination of value stock, growth stock, ascending stock and descending stock. Using the difference of investment performance of these portfolios, when fundamental analysis and technical analysis method all considering we measure investment performance. The major findings of this research are as follows: First, the value strategy of buying value stocks and selling growth stocks were effective in the long-term investment. Second, using the moving average method, technical analysis were effective in the case of the short-term investment. Third, the portfolios combined fundamental analysis and technical analysis were more effective than investment performance of technical analysis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.8
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• pp.1377-1383
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• 2008

Parameterization of a 3D triangular mesh is a fundamental problem in various applications of geometric modeling and computer graphics. There are two major paradigms in mesh parameterization: energy functional minimization and the convex combination approach. In general, the convex combination approach is wifely used because of simple concept and one-to-one mapping. However, the approach has some problems such as high distortion near the boundary and time complexity. Moreover, the stability of the linear system may not be preserved according to the geometric information of the mesh. In this paper, we present an extension of the convex combination approach based on the mean value coordinates, which resolves the drawbacks of the convex combination approach. This may be a more practical solution because it is able to generate a stable linear system in a short time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.522-539
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• 2021

In order to solve the problems of the existing audio fingerprint method when extracting audio fingerprints from long speech segments, such as too large fingerprint dimension, poor robustness, and low retrieval accuracy and efficiency, a robust audio fingerprint retrieval method based on feature dimension reduction and feature combination is proposed. Firstly, the Mel-frequency cepstral coefficient (MFCC) and linear prediction cepstrum coefficient (LPCC) of the original speech are extracted respectively, and the MFCC feature matrix and LPCC feature matrix are combined. Secondly, the feature dimension reduction method based on information entropy is used for column dimension reduction, and the feature matrix after dimension reduction is used for row dimension reduction based on energy feature dimension reduction method. Finally, the audio fingerprint is constructed by using the feature combination matrix after dimension reduction. When speech's user retrieval, the normalized Hamming distance algorithm is used for matching retrieval. Experiment results show that the proposed method has smaller audio fingerprint dimension and better robustness for long speech segments, and has higher retrieval efficiency while maintaining a higher recall rate and precision rate.

• The Research Journal of the Costume Culture
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• v.16 no.5
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• pp.863-877
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• 2008

The purpose of this study is to investigate the effect of dot pattern size(0.8, 1.8, 2.5, 5, 8), color combination (BG/R, Y/B), value tone(lt/dk, p/g), area-ratio on image information. Sets of stimulus and response scales(7 point semantic) were used as experimental materials. The stimuli were 20 color pictures manipulated with the combination of dot pattern size, color combination, value tone and area-ratio using computer simulation. The subjects were 240 female undergraduates living in Gyeongsangnam-do. Image factor of the stimulus was composed of 4 different components, visibility, chastity.feminity, cuteness and attractiveness. In the visibility, color combination, value tone, area-ratio, dot pattern size showed independent effect. In the chastity feminity, color combination, value tone, showed independent effect. In the cuteness, value tone, area-ratio, dot pattern size showed independent effect. Significant interaction effects of color and area-ratio combination on visibility and cuteness were found. Interaction efforts of color and value tone combination, value tone and area-ratio was significant on cuteness. For visibility image, BG/R combination of color and yellow background/blue dots were effective. For cuteness image, pale/grayish tone and background/dots area-ratio were effective.

• Science of Emotion and Sensibility
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• v.21 no.1
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• pp.143-154
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• 2018

This study was performed in order to suggest useful data for color planning of eco-friendly and sensible fashion products. Silk fabrics were dyed in combination with natural indigo and Japanese pagoda tree and were treated with four kinds of mordants after combination dyeing. Then, their colorimetric properties were evaluated. From these composite-dyed silk fabrics, color sensibilities and color preferences of green yellow (GY) color were evaluated among the female university students, and thus, the influences of colorimetric properties and color sensibilities on color preferences were analyzed. When the silk fabrics were dyed in the combination of natural indigo and Japanese pagoda tree and were treated without mordants, they turned green color when indigo 10 g/L was used, and blue-green when indigo 20 g/L was added. And when they were dyed in combination of natural indigo and Japanese pagoda tree and were treated with four kind of mordants after combination dyeing, they turned GY color in almost all cases. The color sensibilities of the GY silk fabrics with the combination dyeing of indigo and Japanese pagoda tree, were classified into three factors: pleasantness, gracefulness, and comfort. Color sensibility factors showed significant differences according to the concentration of indigo and the kinds of mordants. There were almost significant relationships between colorimetric properties and color sensibilities factors of compositely dyed GY silk fabrics. The color preferences of the GY fabrics, which were dyed in the combination of using natural indigo and Japanese pagoda tree and four kinds of mordants, were found to be predicted by the color sensibility in a regression model.

• Journal of Korean language education
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• v.28 no.3
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• pp.153-180
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• 2017

This research examined compound particles, which have not been properly addressed in existing studies on particle combination education, from the perspective of Korean language education as a second language. First, existing research was examined with the understanding of the issue that there is a lack of discussion in existing studies on the education method of either including the compound particle in particle combination or excluding it all together. In the next chapter, an examination was made on the concept and usage of terminology for compound particles in the field of Korean linguistics. Following a summary of this information, a review was made on the list of compound particles established in Korean linguistics. Thus, seven compound particles were identified for Korean language education considering discriminant standard and educational effectiveness from the perspective of Korean language education. The researcher proposes that the compound particle should be taught as an extension of particle combination education and that its concept should be clearly outlined as a direction for future education.