• 제목/요약/키워드: Pattern Similarity

검색결과 554건 처리시간 0.022초

Mathematics Inquiring Based on Pattern Similarity

  • Yanhui Xu
    • 한국수학교육학회지시리즈D:수학교육연구
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    • 제26권3호
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    • pp.147-166
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    • 2023
  • Mathematics is a science of pattern. Mathematics is a subject of inquiring which aims at discovering the models hidden behind the world. Pattern is abstraction and generalization of the model. Mathematical pattern is a higher level of mathematical model. Mathematics patterns are often hidden in pattern similarity. Creation of mathematics lies largely in discovering the pattern similarity among the various components of mathematics. Inquiring is the core and soul of mathematics teaching. It is very important for students to study mathematics like mathematicians' exploring and discovering mathematics based on pattern similarity. The author describes an example about how to guide students to carry out mathematics inquiring based on pattern similarity in classroom.

텍스트 마이닝을 이용한 소비자 소비패턴 분석 기법 설계 (An Analysis Scheme Design of Customer Spending Pattern using Text Mining)

  • 정은희;이병관
    • 한국정보전자통신기술학회논문지
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    • 제11권2호
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    • pp.181-188
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    • 2018
  • 본 논문에서는 텍스트 마이닝을 이용한 소비자의 소비패턴 분석 기법을 제안하였다. 제안하는 소비패턴 분석기법에서는 첫째, 피어슨의 상관계수를 이용하여 사용자의 평가점수에 대한 유사도를 분석하고, 둘째, 텍스트 마이닝 기법 중의 하나의 TD-IDF의 코사인 유사도를 이용하여 사용자의 리뷰들간의 유사도를 분석하고, 셋째, Sentiwordnet를 이용하여 평가점수와 리뷰의 일치성을 분석하였다. 그리고 제안하는 소비패턴 분석 기법은 평가점수의 유사도와 리뷰의 유사도를 이용하여 근접이웃들을 선정하고, 선정된 이웃에 소비패턴에 적합한 추천리스트를 제공하였다. 추천리스트의 정확도는 피어슨 상관계수가 0.79, TD-IDF가 0.73, 그리고 제안하는 소비패턴분석기법이 0.82로 나타났다. 즉, 제안하는 소비패턴분석기법은 소비자의 정량적인 평가점수와 정성적인 리뷰를 모두 이용하므로 소비 패턴을 좀 더 정확하게 분석할 수 있었다.

APPLICATIONS OF SIMILARITY MEASURES FOR PYTHAGOREAN FUZZY SETS BASED ON SINE FUNCTION IN DECISION-MAKING PROBLEMS

  • ARORA, H.D.;NAITHANI, ANJALI
    • Journal of applied mathematics & informatics
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    • 제40권5_6호
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    • pp.897-914
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    • 2022
  • Pythagorean fuzzy sets (PFSs) are capable of modelling information with more uncertainties in decision-making problems. The essential feature of PFSs is that they are described by three parameters: membership function, non-membership function and hesitant margin, with the total of the squares of each parameter equal to one. The purpose of this article is to suggest some new similarity measures and weighted similarity measures for PFSs. Numerical computations have been carried out to validate our proposed measures. Applications of these measures have been applied to some real-life decision-making problems of pattern detection and medicinal investigations. Moreover, a descriptive illustration is employed to compare the results of the proposed measures with the existing analogous similarity measures to show their effectiveness.

A New Class of Similarity Measures for Fuzzy Sets

  • Omran Saleh;Hassaballah M.
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제6권2호
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    • pp.100-104
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    • 2006
  • Fuzzy techniques can be applied in many domains of computer vision community. The definition of an adequate similarity measure for measuring the similarity between fuzzy sets is of great importance in the field of image processing, image retrieval and pattern recognition. This paper proposes a new class of the similarity measures. The properties, sensitivity and effectiveness of the proposed measures are investigated and tested on real data. Experimental results show that these similarity measures can provide a useful way for measuring the similarity between fuzzy sets.

A Study on Finding the Rail Space in Elevators Using Matched Filter

  • Song, Myong-Lyol
    • 한국컴퓨터정보학회논문지
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    • 제24권6호
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    • pp.57-65
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    • 2019
  • In this paper, we study on finding the rail space in elevators by analyzing each image captured with CCD camera. We propose a method that applies one-dimensional matched filter to the pixels of a selected search space in the vertical line at a horizontal position and decides the position with the thickness of the space being represented by a black thick line in captured images. The pattern similarity representing how strongly the associated image pixels resemble with the thick line is defined and calculated with respect to each position along the vertical line of pixels. The position and thickness of the line are decided from the point having the maximum in pattern similarity graph. In the experiments of the proposed method under different illuminational conditions, it is observed that all the pattern similarity graphs show similar shape around door area independent of the conditions and the method can effectively detect the rail space if the rails are illuminated with even weak light. The method can be used for real-time embedded systems because of its simple algorithm, in which it is implemented in simple structure of program with small amount of operations in comparison with the conventional approaches using Canny edge detection and Hough transform.

Open-Ball Scheme을 이용한 2D 패턴의 상대적 닮음 정도 측정의 Moment Invariant Method와의 비교 (Similarity Measurement Using Open-Ball Scheme for 2D Patterns in Comparison with Moment Invariant Method)

  • 김성수
    • 대한전기학회논문지:전력기술부문A
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    • 제48권1호
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    • pp.76-81
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    • 1999
  • The degree of relative similarity between 2D patterns is obtained using Open-Ball Scheme. Open-Ball Scheme employs a method of transforming the geometrical information on 3D objects or 2D patterns into the features to measure the relative similarity for object(patten) recognition, with invariance on scale, rotation, and translation. The feature of an object is used to obtain the relative similarity and mapped into [0, 1] the interval of real line. For decades, Moment-Invariant Method has been used as one of the excellent methods for pattern classification and object recognition. Open-Ball Scheme uses the geometrical structure of patterns while Moment Invariant Method uses the statistical characteristics. Open-Ball Scheme is compared to Moment Invariant Method with respect to the way that it interprets two-dimensional patten classification, especially the paradigms are compared by the degree of closeness to human's intuitive understanding. Finally the effectiveness of the proposed Open-Ball Scheme is illustrated through simulations.

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소셜 네트워크 기반 사용자 유사성 발견을 통한 개인화 및 소셜 검색 (Personalized and Social Search by Finding User Similarity based on Social Networks)

  • 박건우;오정운;이상훈
    • 정보처리학회논문지D
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    • 제16D권5호
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    • pp.683-690
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    • 2009
  • 소셜 네트워크(Social Network)는 웹 환경에서 개인 중심의 네트워크로 구성되어 웹 사용자별 프로파일을 탐색하고 새로운 연결을 형성함으로써 정보의 소통을 지원한다. 따라서 유사한 내재적 정보를 가진 웹 사용자들로 구성 된 소셜 네트워크를 찾아서 검색에 적용한다면 검색의 효율성과 검색 결과에 대한 웹 사용자의 만족도를 향상 시킬 수 있다. 본 논문에서는 첫째, 웹 사용자간 직접 또는 간접적인 연결로 구성된 소셜 네트워크를 구성 한다. 둘째, 사용자들의 속성(Feature)에 내재된 정보를 이용하여 주제(topic)별 웹 사용자 간 유사성(Similarity)을 산정한 후, 주제(Topic)별 변화되는 유사성에 따라 소셜 네트워크를 재구성한다. 마지막으로 산정된 유사성과 웹 사용자들의 검색결과에 대한 만족도, 즉 검색 패턴(Search Pattern)을 비교 실험 한다. 실험 결과 주제별 유사성이 높은 웹 사용자 간에는 검색 패턴 또한 유사함을 확인 하였다. 이와 같은 사실을 검색에 적용한다면 개인화 검색(Personalized Search) 및 소셜 검색(Social Search)의 효율성 및 신뢰성 향상에 기여 할 수 있다.

Distance measure between intuitionistic fuzzy sets and its application to pattern recognition

  • Park, Jin-Han;Lim, Ki-Moon;Kwun, Young-Chel
    • 한국지능시스템학회논문지
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    • 제19권4호
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    • pp.556-561
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    • 2009
  • In this paper, we propose new method to calculate the distance between intuitionistic fuzzy sets(IFSs) based on the three dimensional representation of IFSs and analyze the relations of similarity measure and distance measure of IFSs. Finally, we apply the proposed measures to pattern recognitions.

상대유사도를 이용한 새로운 무감독학습 신경망 및 경쟁학습 알고리즘 (A New Unsupervised Learning Network and Competitive Learning Algorithm Using Relative Similarity)

  • 류영재;임영철
    • 한국지능시스템학회논문지
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    • 제10권3호
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    • pp.203-210
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    • 2000
  • 본 논문에서는 패턴분류문제를 해결하기 위한 새로운 무감독학습 신경망 및 경쟁학습 알고리즘을 제한한다. 제아하는 신경망은 입력 데이터의 군집을 분류하기 위한 거리측도로서 군집들 상호간의 상대유사도(relative similarity)를 기반으로 하고 있다. 이러한 까닭에 제안하는 신경망과 알고리즘을 상대유사 신경망 (relative similarity network; RSN)및 학습 알고리즘이라 이름한다. 상대유사도를 정의하고 가중벡터 학습 규칙을 구성함으로써, RSN의 구조를 설계하고 학습알고리즘을 구현하기 의한 의사코드를 기술한다. 일반적인 패턴분류에 RSN을 적용한 결과, 초기 학습률이 없음에도 불구하고 기존이 경쟁학습 신경망인 WTAdlsk SOM고 동등한 성능을 나타내었다. 반면 기존 경쟁학습 신경망의 분류성능이 저하되었던 군집이 경걔가 불분명한 패턴, 그리고 군집이 밀집도와 군집의 크기가 다른 패턴들에 대한 실험에서는 기존의 경쟁학습망보다 효과적인 분류결과를 나타내었다.

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A Heuristic Methodology for Fault Diagnosis using Statistical Patterns

  • Kwon, Young-il;Song, Suh-ill
    • 품질경영학회지
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    • 제21권2호
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    • pp.17-26
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    • 1993
  • Process fault diagnosis is a complicated matter because quality control problems can result from a variety of causes. These causes include problems with electrical components, mechanical components, human errors, job justification errors, and air conditioning influences. In order to make the system run smoothly with minimum delay, it is necessary to suggest heuristic remedies for the detected faults. Hence, this paper describes a heuristic methodology of fault diagnosis that is performed using statistical patterns generated by quality characteristics The proposed methodology is described briefly as follows: If a sample pattern generated by random variables is similar to the number of prototype patterns, the sample pattern may be matched by any prototype pattern among them to be resembled. This concept is based on the similarity between a sample pattern and the matched prototype pattern. The similarity is calculated as the weighted average of squared deviation, which is expressed as the difference between the relative values of standard normal distribution to be transformed by the observed values of quality characteristics in a sample pattern and the critical values of the corresponding ones in a matched prototype pattern.

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