• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.177-192
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• 2012

This is a study of match-making systems that considers the mutual satisfaction of matching partners. Recently, recommendation systems have been applied to people recommendation, such as recommending new friends, employees, or dating partners. One of the prominent domain areas is match-making systems that recommend suitable dating partners to customers. A match-making system, however, is different from a product recommender system. First, a match-making system needs to satisfy the recommended partners as well as the customer, whereas a product recommender system only needs to satisfy the customer. Second, match-making systems need to include as many participants in a matching pool as possible for their recommendation results, even with unpopular customers. In other words, recommendations should not be focused only on a limited number of popular people; unpopular people should also be listed on someone else's matching results. In product recommender systems, it is acceptable to recommend the same popular items to many customers, since these items can easily be additionally supplied. However, in match-making systems, there are only a few popular people, and they may become overburdened with too many recommendations. Also, a successful match could cause a customer to drop out of the matching pool. Thus, match-making systems should provide recommendation services equally to all customers without favoring popular customers. The suggested match-making system, called Mutually Beneficial Matching (MBM), considers the reciprocal satisfaction of both the customer and the matched partner and also considers the number of customers who are excluded in the matching. A brief outline of the MBM method is as follows: First, it collects a customer's profile information, his/her preferable dating partner's profile information and the weights that he/she considers important when selecting dating partners. Then, it calculates the preference score of a customer to certain potential dating partners on the basis of the difference between them. The preference score of a certain partner to a customer is also calculated in this way. After that, the mutual preference score is produced by the two preference values calculated in the previous step using the proposed formula in this study. The proposed formula reflects the symmetry of preferences as well as their quantities. Finally, the MBM method recommends the top N partners having high mutual preference scores to a customer. The prototype of the suggested MBM system is implemented by JAVA and applied to an artificial dataset that is based on real survey results from major match-making companies in Korea. The results of the MBM method are compared with those of the other two conventional methods: Preference-Based Matching (PBM), which only considers a customer's preferences, and Arithmetic Mean-Based Matching (AMM), which considers the preferences of both the customer and the partner (although it does not reflect their symmetry in the matching results). We perform the comparisons in terms of criteria such as average preference of the matching partners, average symmetry, and the number of people who are excluded from the matching results by changing the number of recommendations to 5, 10, 15, 20, and 25. The results show that in many cases, the suggested MBM method produces average preferences and symmetries that are significantly higher than those of the PBM and AMM methods. Moreover, in every case, MBM produces a smaller pool of excluded people than those of the PBM method.

• The Journal of Korean Association of Computer Education
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• v.14 no.2
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• pp.83-94
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• 2011

In the biomedical domain, the longest matching method is frequently used for recognizing named entity written in the literature. This method uses a dictionary as a resource for named entity recognition. If there exist appropriated dictionary about target domain, the longest matching method has the advantage of being able to recognize the entities of target domain quickly and exactly. However, the longest matching method is difficult to recognize the enumerated named entities, because these entities are frequently expressed as being omitted some words. In order to resolve this problem, we propose the partial matching method using a dictionary. The proposed method makes several candidate entities on the assumption that the ellipses may be included. After that, the method selects the most valid one among candidate entities through the optimization algorithm. We tested the longest and partial matching method about HLA entities: HLA gene, antigen, and allele entities, which are frequently enumerated among biomedical entities. As preparing for named entity recognition, we built two new resource, extended dictionary and tag-based dictionary about HLA entities. And later, we performed the longest and partial matching method using each dictionary. According to our experiment result, the longest matching method was effective in recognizing HLA antigen entities, in which the ellipses are rare, and the partial matching method was effective in recognizing HLA gene and allele entities, in which the ellipses are frequent. Especially, the partial matching method had a high F-score 95.59% about HLA alleles.

• Journal of Korean Clinical Nursing Research
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• v.25 no.2
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• pp.142-150
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• 2019

Purpose: The aim of this study was to evaluate the efficiency of the Humpty Dumpty Falls Scale as one of the falls risk assessment tools, and also to evaluate risk factors as predictors of falls in pediatric patient populations. Methods: In a retrospective, case-control design with data from the electronic medical records of 13 pediatric patients who fell and 1,941 who did not fall before matching and 429 who did not fall after matching by gender, age, diagnosis, and length of stay. Results: All the variables showed no significant differences after matching. At the cutoff score of 13, sensitivity, specificity, negative and positive predictive values were 92.3%, 37.1%, 99.9%, and 0.01%, respectively. The area under the Receiver Operating Characteristics was 0.597. The results from the logistic regression showed that the pediatric inpatient population who had higher risk scores was significantly associated with falls. The odds ratios ranged from 1.31 to 4.71 with 90% confidence interval. Conclusion: The saturation impairments criterion as one of the diagnostic parameter was negatively associated with falls, but the relative risk score was higher than the other criteria. Therefore, it seems that the diagnostic parameter seems to be required to verify results through large sample studies.

• Korea Trade Review
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• v.44 no.3
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• pp.227-252
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• 2019

This study explores the effects of exports on the innovation of Korean firms listed on two Korean stock markets, the Korean Stock Exchange and the Korean Securities Dealers Quotations, between 1999 and 2016. By matching exporting firms to non-exporting ones with propensity score matching, this study accounts for a problem from sample selection bias that may arise from differences in firm-characteristics between the two groups. From the study results, first, both export participation and export volume significantly increase subsequent innovation performance, as measured by the number of patent applications. This result seems to support the "learning by exporting" hypothesis for Korean listed firms. Second, both export participation and export volume narrow innovation scope, proxied as the number of unique International Patent Classification (IPC) codes of the patent applied, the degree to which patents are concentrated in a particular class, and the degree of proximity in the patents. The findings of innovation scope suggest a possible explanation that the learning effect appears in familiar technology fields that firms have previously held, rather than in unfamiliar ones. Third, these results are robust using alternative proxies in the innovation scope, Tobit regressions to consider the non-trivial portion of sample firms with patent applications equal to zeros, and generalized method of moments (GMM) to control for the persistence of innovation measures hearing over years. Finally, the two main results are more pronounced in large firms than in small and medium-sized ones. As for Chaebol firms, however, these results do not appear.

• The Korean Journal of Applied Statistics
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• v.30 no.3
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• pp.453-462
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• 2017

Double propensity score adjustment is an analytic solution to address bias due to incomplete matching. However, it is difficult to estimate the standard error of the estimated treatment effect when using double propensity score adjustment. In this study, we propose two bootstrap methods to estimate the standard error. The first is a simple bootstrap method that involves drawing bootstrap samples from the matched sample using the propensity score as well as estimating the standard error from the bootstrapped samples. The second is a complex bootstrap method that draws bootstrap samples first from the original sample and then applies the propensity score matching to each bootstrapped sample. We examined the performances of the two methods using simulations under various scenarios. The estimates of standard error using the complex bootstrap were closer to the empirical standard error than those using the simple bootstrap. The simple bootstrap methods tended to underestimate. In addition, the coverage rates of a 95% confidence interval using the complex bootstrap were closer to the advertised rate of 0.95. We applied the two methods to a real data example and found also that the estimate of the standard error using the simple bootstrap was smaller than that using the complex bootstrap.

• The Journal of Fisheries Business Administration
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• v.48 no.4
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• pp.11-25
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• 2017

The purpose of the study is to analyze the status and trend of less favored condition of fishing village in Korean island regions using the census of agriculture, forestry and fisheries. The less favored condition was measured as the difference in accessibility to major services and in fishery sales and resident infrastructure, applying the difference-in-difference method and propensity score matching method respectively. The result shows that access to major services has improved in island area between 2010 and 2015, implying that related policies such as the island comprehensive development project have been successful to some extent. However, some educational facilities, cultural facilities, and health facilities still have low inaccessibility and fishery sales are also significantly lower than in general area. This suggests that it is necessary to maintain related policies like the direct payment of fisheries.

• 한국벤처창업학회:학술대회논문집
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• 2021.11a
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• pp.113-117
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• 2021

Due to the recent COVID-19 pandemic, SMEs are forced to converge themselves into online business to cope with the rapidly changing business environment. However, due to various difficulties of becoming an online business, most SMEs choose to use services provided by the online sales platform. These platforms offer valuable support such as DSS in return for the high amount of commission fee. We analyze a novel data set from Naver Corporation's 'Smart Store' platform with the quasi-experimental method (propensity score matching technique combined with the difference in differences analysis) to analyze DSS usage and SME's performance empirically. Our results suggest that DSS usage leads to an increase in SME's sales performance in means of sales frequency and sales amount. Additionally, we have found weak support that DSS usage enables SMEs to attract customers better than those not using DSS.

• Korea Trade Review
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• v.46 no.2
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• pp.323-335
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• 2021

With the advent of the 4th Industrial Revolution, there is a rising interest in the impact of these changes on Korea's trade. While the previous studies related to the 4th Industrial Revolution are very limited in the field of trade research, this study attempts an empirical analysis regarding the effect of the use of the 4th Industrial Revolution technology on the performance of exporters, based on the data of the Survey of Business Activities during 2017-2019 by the Korean government statistical office. Through the empirical analysis in combination with the propensity score matching (PSM) and the difference-in-difference (DID) analysis, this research confirms that the use of the 4th Industrial Revolution technology has a positive effect on the export performance of Korean exporters.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.450-455
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• 2009

Amplitude-only logarithmic Radon transform (ALR transform) for pattern matching is proposed. This method provides robustness for object translation, scaling, and rotation. An ALR image is invariant even if objects are translated in a picture. For the object scaling and rotation, the ALR image is merely translated. The objects are identified using a phase-only matched filter to the ALR image. The ratio of size, the difference of rotation angle, and the position between the two objects are detected. Our pattern matching procedure is described, herein, and its simulation is executed. We compare matching scores with the Fourier-Mellin transform, and the general phase-only matched filter.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.9
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• pp.868-874
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• 2007

This paper proposes an efficient partial matching system and representation by using a region-based method for 2D image, and we applied to an extraction of the ROI(Region of Interest) according to its matching score. The matching templates consist of the global pattern and the local one. The global pattern can make it by using region-based relation between center region and its rest regions in an object. And, the local pattern can be obtained appling to the same method as global, except relation between objects. As the templates can be normalized, we use this templates for extraction of ROI with invariant to size and position. And, our system operates only one try to match, due to normalizing of region size. To use our system for searching and examining if it's the ROI by evaluating the matching function, at first, we are searching to find candidate regions with the global template. Then, we try to find the ROI among the candidates, and it works this time by using the local template. We experimented to the binary and the color image respectively, they showed that the proposed system can be used efficiently for representing of the template and the useful applications, such as partially retrievals of 2D image.