• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2002.11a
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• pp.224-228
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• 2002

제품의 품질 및 가격 뿐만 아니라 물질적 풍요로움과 더불어 다변화 되어가는 생활 환경 속에서 소비자의 감성과 선호도를 파악하는 것은 제품 판매 전략의 중요한 성공요소가 되고 있다. 이를 위하여 제품의 기능적 측면 뿐만 아니라 개개인의 정서적 감정과 선호도가 반영된 제품의 설계나 디자인 또한 요구되고 있다. 본 연구에서는 소재 개발의 프로세스가 고객 중심으로 변화하는 것에 대응하여 사용자의 감성과 선호도를 중심으로 소재를 개발하는 방법의 하나로 협력적 필터링 개인화 기법을 응용하여 섬유 패션 디자인 추천 시스템을 제안한다. Textile 기반의 협력적 필터링 시스템에서 예측에 사용될 이웃의 수를 결정하기 위해서 Representative Attribute-Neighborhood를 사용한다. 이웃들간의 사용자 유사도 가중치는 피어슨 상관 계수(Pearson Correlation Coefficient)를 사용한다. 소재에 대한 사용자의 감성이나 선호도에 대한 Textile의 대표 감성 형용사를 추출함으로써 소재 개발을 위한 감성 형용사 데이터 베이스를 구축한다. 구축된 감성 형용사 데이터 베이스를 기반으로 성향이 비슷한 사용자에게 Textile을 추천한다. 사용자 선호도 예측과 Textile 기반의 협력적 필터링 기술을 이용한 섬유 패션 디자인 추천 에이전트를 구축하여 시스템의 논리적 타당성과 유효성을 검증하기 위해 실험적인 적용을 시도하고자 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.04a
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• pp.554-557
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• 2016

2015년 우리나라 스마트폰 보급률이 83%에 다다르고 인터넷 정보 검색은 PC보다 모바일이 추월한지 오래다. 범람하는 정보 안에서 편하고 빠른 것에 익숙해진 사용자들은 이제 개인화된 맞춤형 추천 정보의 제공을 원한다. 맞춤형 추천을 위해서는 사용자의 행동을 이해하고 추천하는 것이 필요하다. 현재 대중화된 개인 추천 서비스는 책과 영화가 있는데 생활에 많은 부분을 차지하고 있는 음식점 방문에 대해서도 맞춤형 추천 서비스를 제공해 줄 수 있다. 본 논문에서는 음식점 방문에 대한 비슷한 태도를 보인 사용자를 추출한 후 방문했던 장소를 비교하여 추천하는 사용자 행동 기반 다속성 태도 모델 기반의 장소 추천 모델을 연구한다. 다속성 태도점수를 산출하기 위해 피쉬바인(Fishbein) 방정식을 활용하고 피어슨 상관계수를 이용하여 사용자들간의 유사한 장소를 추출했다. 그리고 그룹렌즈의 선호도 예측 알고리즘을 활용하여 추천 대상 장소를 선정하고 유클라디안 거리법으로 사용자의 거리기반 장소를 추천하였다. 또한 본 논문에서는 실제 데이터를 이용한 실험을 통해 본 논문에서 제시한 시스템의 우수성도 입증하였다.

• Smart Media Journal
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• v.5 no.2
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• pp.84-89
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• 2016

For a place-recommendation model based on user's behavior and multi-attribute attitude in this thesis. We focus groups that show similar patterns of visiting restaurants and then compare one and the other. We make use of The Fishbein Equation, Pearson's Correlation Coefficient to calculate multi-attribute attitude scores. Furthermore, We also make use of Preference Prediction Algorithm and Distance based method named "Euclidean Distance" to provide accurate results. We can demonstrate how excellent this system is through several experiments carried out with actual data.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.2
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• pp.193-200
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• 2022

Unknown cryptographic communication protocols may have advantage of guaranteeing personal and data privacy, but when used for malicious purposes, it is almost impossible to identify and respond to using existing network security equipment. In particular, there is a limit to manually analyzing a huge amount of traffic in real time. Therefore, in this paper, we attempt to identify packets of unknown cryptographic communication protocols and separate fields comprising a packet by using machine learning techniques. Using sequential patterns analysis, hierarchical clustering, and Pearson's correlation coefficient, we found that the structure of packets can be automatically analyzed even for an unknown cryptographic communication protocol.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.5
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• pp.2981-2988
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• 2014

The Purpose of the this study was to identify reliability and validity of the Korean version of the Swallowing Quality of Life questionnaire(KSWAL-QOL). The study was performed in 71 patients diagnosed dysphagia by videofluoroscopy and 80 healthy swallowers. The reliability was good with a Cronbach's ${\alpha}$ and intraclass correlation coefficient of .86~.96 and .80~.93, respectively. The Pearson product moment correlation coefficients between KSWAL-QOL scales ranged from .17~.74 which was showed significant correlation. Healty swallowers scored higher than dysphagic patients on all scales and statistically significant differences were observed across all the scales between healthy swallowers and dysphagic patients(p<.01). Tube feeders scored lower than non-tube feeders on all scales and statistically significant differences were observed in all the scales except sleep(p<.05). There are significant difference between diet steps in all scales except eating desire, communication, fear and people on diet fourth step feeding had the highest scores on the all scales(p<.05). Because KSWAL-QOL seems to be a reliable and valid tool, it is considered to be appropriate as a tool to measure quality of life of patient with swallowing disorder.

• Journal of KIISE:Software and Applications
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• v.30 no.3_4
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• pp.316-325
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• 2003

A user preference prediction method using an exiting collaborative filtering technique has used the nearest-neighborhood method based on the user preference about items and has sought the user's similarity from the Pearson correlation coefficient. Therefore, it does not reflect any contents about items and also solve the problem of the sparsity. This study suggests the preference prediction system using the similarity weight granted Bayesian estimated value and the associative user clustering to complement problems of an exiting collaborative preference prediction method. This method suggested in this paper groups the user according to the Genre by using Association Rule Hypergraph Partitioning Algorithm and the new user is classified into one of these Genres by Naive Bayes classifier to slove the problem of sparsity in the collaborative filtering system. Besides, for get the similarity between users belonged to the classified genre and new users, this study allows the different estimated value to item which user vote through Naive Bayes learning. If the preference with estimated value is applied to the exiting Pearson correlation coefficient, it is able to promote the precision of the prediction by reducing the error of the prediction because of missing value. To estimate the performance of suggested method, the suggested method is compared with existing collaborative filtering techniques. As a result, the proposed method is efficient for improving the accuracy of prediction through solving problems of existing collaborative filtering techniques.

• The Journal of Korean Academy of Sensory Integration
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• v.16 no.3
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• pp.11-21
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• 2018

Objective : The purpose of this study is to investigate correlation of sensory processing patterns, learning styles and learning strategies for university students. Methods : Participants of this study are 115 students from K university in Busan, South Korea. Measurements are Adolescent/Adult Sensory Profile (AASP) for sensory processing patterns, the Study Process Questionnaire (SPQ) for learning styles, and the Motivated Strategies for Learning Questionnaire (MSLQ) for learning strategies. The data collected was analyzed by SPSS/WIN 20.0 for chisuare test and Pearson corelation coefficient. Results : For sensory processing patterns and learning styles, there were correlation between low registration type and surface type of learning (p=0.03), and between sensory seeking type and deep type of learning (p=0.02). For sensory processing patterns and learning strategies, sensory seeking type was correlated with organized learning strategy (p=0.00), and sensory sensitivity type was correlated with organizational learning strategy (p=0.03) and meta-cognitive learning strategy (p=0.00). Conclusion : This study found that there is correlation between sensory processing patterns, learning styles and learning strategies with implying learning styles and learning strategies can be different depends on sensory procession pattern. The results of this study can be used as a basic data to select learning type and learning strategy appropriate for an individual based on his or her sensory processing patterns.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.7
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• pp.1243-1248
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• 2008

As development in technology of bioinformatics recently mates it possible to operate micro-level experiments, we can observe the expression pattern of total genome through on chip and analyze the interactions of thousands of genes at the same time. In this thesis, we used CDNA microarrays of 3840 genes obtained from neuronal differentiation experiment of cortical stem cells on white mouse with cancer. It analyzed and compared performance of each of the experiment result using existing DT, NB, SVM and multi-perceptron neural network classifier combined the similar scale combination method after constructing class classification model by extracting significant gene list with a similar scale combination method proposed in this paper through normalization. Result classifying in Multi-Perceptron neural network classifier for selected 200 genes using combination of PC(Pearson correlation coefficient) and ED(Euclidean distance coefficient) represented the accuracy of 98.84%, which show that it improve classification performance than case to experiment using other classifier.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.12
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• pp.2259-2264
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• 2008

Significant genes are defined as genes in which the expression level characterizes a specific experimental condition. Such genes in which the expression levels differ significantly between different groups are highly informative relevant to the studied phenomenon. In this paper, first the system can detect informative genes by similarity scale combination method being proposed in this paper after normalizing data with methods that are the most widely used among several normalization methods proposed the while. And it compare and analyze a performance of each of normalization methods with multi-perceptron neural network layer. The Result classifying in Multi-Perceptron neural network classifier for selected 200 genes using combination of PC(Pearson correlation coefficient) and ED(Euclidean distance coefficient) after Lowess normalization represented the improved classification performance of 98.84%.

• Journal of the Korean Society for information Management
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• v.19 no.1
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• pp.163-187
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• 2002

The objective of this study was not only to evaluate different academic library homepages but to hit upon and suggest a reformation plan for their future improvement. For this purpose. academic library web pages of Korea were divided into three major groups -- those of national universities, private ones, and junior colleges. Their web pages were evaluated using a number of criteria. Also, their circumstances and problems were tried to grasp and the methods to be corrected were suggested in this thesis. Literature review were performed for this study and suggestions and advices from professional groups that is called Delphi method were used as a tool to achieve the objective of this study. For a basic analysis, frequency analysis and descriptive statistics were used for analysing data. Also, t-test, ANOVA, and chi-square analysis were used to examine whether there are any significant differences in each groups or not. and Pearson product-moment correlation coefficients were used to find out the correlation among several variables.