• Proceedings of the Korean Information Science Society Conference
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• 2001.04b
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• pp.268-270
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• 2001

전자상거래에서 최근 대부분의 개인화된 추천 에이전트 시스템들은 협동적 필터링 기술을 적용하고 있다. 이 방법은 고객의 취향에 맞는 상품을 예측하고 추천하기 위하여 비슷한 선호도를 가지는 다른 고객들과의 상관 관계를 구하기 위하여 일반적으로 피어슨 상관 계수를 이용한다. 그러나 이 방법은 오직 두 고객 사이에서 두 고객 모두 평가를 한 상품이 있을 때에만 상관 관계를 구할 수 있으므로 예측의 정확성이 떨어질 수 있다. 본 논문에서는 이러한 이웃 선정 방법에 대한 문제점을 보완하기 위하여 비슷한 선호 패턴을 가지는 고객들를 보다 적절히 군집화하여 이 군집에 속한 고객들의 평가를 기반으로 협동적 필터링 기술을 수행하는 방법을 제안하고, 기존의 협동적 필터링 기술과의 비교 실험을 통해 성능을 평가 하였다. 실험결과 본 논문에서 제안한 방법이 기존의 방법보다 우수함을 확인할 수 있었다.

• Information Systems Review
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• v.9 no.1
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• pp.85-103
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• 2007

The purpose of this study is to evaluate the performance of collaborative filtering recommender algorithms for better prediction accuracy of the customer's preference. The accuracy of customer's preference prediction is compared through the MAE of neighborhood based collaborative filtering algorithm and correspondence mean algorithm. It is analyzed by using MovieLens 1 Million dataset in order to experiment with the prediction accuracy of the algorithms. For similarity, weight used in both algorithms, commonly, Pearson's correlation coefficient and vector similarity which are used generally were utilized, and as a result of analysis, we show that the accuracy of the customer's preference prediction of correspondence mean algorithm is superior. Pearson's correlation coefficient and vector similarity used in two algorithms are calculated using the preference rating of two customers' co-rated movies, and it shows that similarity weight is overestimated, where the number of co-rated movies is small. Therefore, it is intended to increase the accuracy of customer's preference prediction through expanding the number of the existing co-rated movies.

• Journal of the Korean Solar Energy Society
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• v.39 no.6
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• pp.55-65
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• 2019

With the rapid development of the national industry, the importance of electrical safety was recognized because of a lot of new electrical equipment are installing and the electrical accidents have been occurring annually. Today, the electrical equipments is inspect by using the portable Infrared thermal imaging camera. but the most negative element of using the camera is inspected for only state of heating, the reliable diagnosis is depended with inspector's knowledge, and real-time monitoring is impossible. This paper present the infrared thermal imaging safety diagnosis system. This system is able to monitor in real time, predict the state of fault, and diagnose the state with analysis of thermal and power data. The system consists of a main processor, an infrared camera module, the power data acquisition board, and a server. The diagnostic algorithm is based on a mathematical model designed by analyzing the Pearson's Correlation Coefficient between temperature and power data. To test the prediction algorithm, the simulations were performed by damaging the terminals or cables on the switchboard to generate a large amount of heat. Utilizing these simulations, the developed prediction algorithm was verified.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.2
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• pp.181-188
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• 2018

In this paper, we propose an analysis scheme of customer spending pattern using text mining. In proposed consumption pattern analysis scheme, first we analyze user's rating similarity using Pearson correlation, second we analyze user's review similarity using TF-IDF cosine similarity, third we analyze the consistency of the rating and review using Sendiwordnet. And we select the nearest neighbors using rating similarity and review similarity, and provide the recommended list that is proper with consumption pattern. The precision of recommended list are 0.79 for the Pearson correlation, 0.73 for the TF-IDF, and 0.82 for the proposed consumption pattern. That is, the proposed consumption pattern analysis scheme can more accurately analyze consumption pattern because it uses both quantitative rating and qualitative reviews of consumers.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.2
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• pp.277-284
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• 2017

In a flood of information, most users will want to get a proper recommendation. If a recommender system fails to give appropriate contents, then quality of experience (QoE) will be drastically decreased. In this paper, we propose a recommender system based on the intra-cluster users' item preference for improving recommendation accuracy indices such as precision, recall, and F1 score. To this end, first, users are divided into several clusters based on the actual rating data and Pearson correlation coefficient (PCC). Afterwards, we give each item an advantage/disadvantage according to the preference tendency by users within the same cluster. Specifically, an item will be received an advantage/disadvantage when the item which has been averagely rated by other users within the same cluster is above/below a predefined threshold. The proposed algorithm shows a statistically significant performance improvement over the item-based collaborative filtering algorithm with no clustering in terms of recommendation accuracy indices such as precision, recall, and F1 score.

• Journal of Information Management
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• v.40 no.2
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• pp.95-115
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• 2009

Author resolution is to disambiguate same-name author occurrences into real individuals. For this, pair-wise author similarities are computed for author name entities, and then clustering is performed. So far, many studies have employed hierarchical clustering techniques for author disambiguation. However, various hierarchical clustering methods have not been sufficiently investigated. This study covers an empirical evaluation and analysis of hierarchical clustering applied to Korean author resolution, using multiple distance functions such as Dice coefficient, Cosine similarity, Euclidean distance, Jaccard coefficient, Pearson correlation coefficient.

• Journal of Broadcast Engineering
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• v.16 no.2
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• pp.331-338
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• 2011

In this paper, we propose a visual fatigue prediction metric which considers individual fusional characteristics for stereoscopic video. It predicts the visual fatigue level by examining the disparity and motion characteristics of 3D videos. In addition, we classified the viewers into 2 groups according to fusional limit and the slope of fusional response which are acquired from random dot stereogram test. Then, Pearson's and Spearman's correlation coefficient was measured between the proposed metrics and the subjective results, acquiring 80% and 79%.

• Composites Research
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• v.35 no.1
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• pp.42-46
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• 2022

In this study, when the carbon fiber composite was manufactured, the correlation between the porosity and mechanical properties according to the number of glass fiber felts laminated together and the stacking sequence was confirmed. The carbon fiber composite was manufactured by stacking glass fiber felts, which are highly permeable materials, and using vacuum assisted resin transfer molding (VARTM). Porosity was measured by photographing the cross-section of the specimen with an optical microscope and then using porosity calculation code of MATLAB, and mechanical properties were measured for tensile strength, modulus by tensile test. Furthermore, Pearson correlation coefficient between porosity and mechanical properties was calculated to confirm the correlation between two variables. As a result, the number of glass fiber felt increased and the distance from the center of laminated composites increased, the porosity increasing were confirmed. In addition, tensile strength/modulus showed a weak positive correlation with porosity. Also, in order to confirm the effect of only porosity on tensile strength and modulus, mechanical properties calculated by CLPT (Classical Laminate Plate Theory) and experimental values were compared, and the difference in tensile strength showed a strong positive correlation with porosity and the difference in modulus showed a weak positive correlation with porosity.

• The Journal of Korean Academy of Sensory Integration
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• v.21 no.3
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• pp.27-38
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• 2023

Objective : This study aims to verify the validity and reliability of the Korean version of the Sensory Processing and Self-Regulation Checklist (SPSRC) for children with and without autism spectrum disorder. Methods : The Pearson product-moment correlation coefficient was calculated using Short Sensory Profile (SSP) to verify concurrent validity. Construct validity was verified by comparing the sensory processing ability and self-regulation ability of the two groups. Cronbach's α was calculated in the case of internal consistency for reliability verification, and the test-retest reliability was verified through the Pearson correlation coefficient. Results : Based on the verification of the concurrent validity, the Korean version of SPSRC and SSP showed a statistically significant correlation (p < 0.01). The construct validity was found to have a statistically significant difference between the two groups in the area and sub-items of the Korean version of SPSRC (p < 0.001). For the internal consistency, Cronbach's α ranged from 0.700 to 0.975. The test-retest reliability showed that the correlation coefficient ranged from 0.937 to 0.997. Conclusion : The Korean version of SPSRC was confirmed to be an evaluation tool with high validity and reliability. It is expected to be used as an evaluation tool for planning treatment goals in clinical trials and as a meaningful basis for future research.

• Journal of Families and Better Life
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• v.12 no.1
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• pp.117-131
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• 1994

본 연구는 근린환경에 대한 거주자의 인지도를 파악하고, 현재 거주하고있는 지역의 근린환경에 대한 만족도를 조사하여 앞으로의 주거이동 성향이 어떻게 나타날 것인가를 예측해보는데 그 목적이 있다. 측정도구의 신뢰도계수($Cronbach's\;\alpha$)는 0.865이며, 분석방법은 빈도, 평균, $x^2$ 검증, t-검증, 일원변령분석 요인분석, 피어슨의 상관계수, 중다회귀분석, 다변량판별분석을 사용하였다. 연구결과는 첫째 '입지성' 속성에 대해 거주자의 인지와 만족이 가장 긍정적이었고 '쾌적성 및 정체감' 에 대해 가정 부정적이었다. 둘째 근린환경 인지도가 높을수록 부인의 교육수준이 높을수록 주거소유권이 자가이고 상가주변지역에 살고 있는 거주자들의 근린환경에 대한 총 만족도가 높게 나타났다. 셋째 거주기간 총 만족도, 주거용도 지역, 주택규모, 소득수준이 주거이동 성향을 판별하는 변인으로 나타났다.