• 한국동물학회지
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• 제24권2호
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• pp.91-98
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• 1981

Deer mice, Peromyscus maniculatus, 의 성체 571마리의 30개 morphometric 형질들을 이용한 cluster analyses에서 두가지의 similarity 행렬식 (Average taxonomic distance와 Correlation coefficient 행렬식)을 이용한 dendrogram이 서로 다르다는 것이 확인되었다. 이들 두가지의 행렬식 중에서 taxarks의 형태적인 유연관계를 나타내는 하나의 dendrogram만을 선택하기 위한 한 객관적방법이 제안되었다. 즉 principal component analysis에 의한 결과를 비교할 표준결과로 이용하는 방법이다.

• 대한수학회보
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• 제58권3호
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• pp.637-657
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• 2021

In this paper, we decompose (under unitary similarity) the Kronecker sum A ⊞ A (= A ⊗ I + I ⊗ A) into a direct sum of irreducible matrices, when A is a 3×3 matrix. As a consequence we identify 𝒦(A⊞A) as the direct sum of several full matrix algebras as predicted by Artin-Wedderburn theorem, where 𝒦(T) is the unital algebra generated by Tand T^*.

• 한국컴퓨터산업학회논문지
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• 제4권10호
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• pp.587-598
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• 2003

본 연구에서는 학술논문을 대상으로 하여 표제와 초록에 대한 2단계 색인어 유사관계행렬을 구축하였다. 동시출현빈도 기반으로 구축된 색인어 유사관계행렬은 호환관계에 따른 질의 확장으로 재현률을 유지하면서 2단계 내용기반 검색으로 정확률을 향상시키기 위한 색인구조이다. 따라서, 주제 분석을 통해 영역지식을 추출하고 이용자의 정보 요구와 영역지식을 퍼지논리 기반으로 추론하였다. 본 연구는 질의에 본질적으로 가지고 있는 용어 불일치 및 정보표현을 향상시키기 위한 연구이다.

• East Asian mathematical journal
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• 제23권2호
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• pp.207-212
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• 2007

We describe the class of invertible matrices T such that $TAT^{-1}$ is EPr, for a given EPr matrix A of order n. Necessary and sufficient condition is determined for $TAT^{-1}$ to be EP for an arbitrary matrix A of order n.

• 대한수학회지
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• 제59권5호
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• pp.997-1013
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• 2022

In this paper we give conditions on a matrix which guarantee that it is similar to a centrosymmetric matrix. We use this conditions to show that some 4 × 4 and 6 × 6 Toeplitz matrices are similar to centrosymmetric matrices. Furthermore, we give conditions for a matrix to be similar to a matrix which has a centrosymmetric principal submatrix, and conditions under which a matrix can be dilated to a matrix similar to a centrosymmetric matrix.

• 한국정보과학회논문지:소프트웨어및응용
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• 제31권11호
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• pp.1519-1533
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• 2004

웹 기반의 학술분야 전문 검색 시스템은 사용자의 정보 요구 표현을 극히 제한적으로 허용함으로써 검색된 정보의 내용 분석과 정보 습득의 과정이 일관되지 못해 무분별한 정보 제공이 이루어진다. 본 논문에서는 용어의 상대적인 중요 정도를 축소용어 집합으로 구성하여 검색 시스템의 높은 시간 복잡도를 해결할 수 있도록 퍼지 검색 모델을 적용하였다. 또한 퍼지 호환관계의 특성을 만족하는 유사관계 행렬을 통해 사용자 질의를 정확하게 반영할 수 있도록 클러스터 검색을 수행하였다. 본 논문에서 제안한 퍼지 검색과 문서 클러스터 검색의 유사도 결합을 통한 순위 재조정 검색 모델은 검색 성능을 표현하는 정확률과 재현율 척도에서 향상됨을 입증하였다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2010년도 추계학술발표대회
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• pp.705-708
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• 2010

An eigen color co-occurrence approach is proposed that exploits the correlation between color channels to identify the degree of image similarity. This method is based on traditional co-occurrence matrix method and histogram equalization. On the purpose of feature extraction, eigen color co-occurrence matrices are computed for extracting the statistical relationships embedded in color images by applying Principal Component Analysis (PCA) on a set of color co-occurrence matrices, which are computed on the histogram equalized images. That eigen space is created with a set of orthogonal axes to gain the essential structures of color co-occurrence matrices, which is used to identify the degree of similarity to classify an input image to be tested for various purposes. In this paper RGB, Gaussian color space are compared with grayscale image in terms of PCA eigen features embedded in histogram equalized co-occurrence features. The experimental results are presented.

• Journal of applied mathematics & informatics
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• 제5권3호
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• pp.717-734
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• 1998

In the present paper is presented a new matrix pencil-based numerical approach achieving the computation of the elemen-tary divisors of a given matrix $A \in C^{n\timesn}$ This computation is at-tained without performing similarity transformations and the whole procedure is based on the construction of the Piecewise Arithmetic Progression Sequence(PAPS) of the associated pencil $\lambda I_n$ -A of matrix A for all the appropriate values of $\lambda$ belonging to the set of eigenvalues of A. This technique produces a stable and accurate numerical algorithm working satisfactorily for matrices with a well defined eigenstructure. The whole technique can be applied for the computation of the first second and Jordan canonical form of a given matrix $A \in C^{n\timesn}$. The results are accurate for matrices possessing a well defined canonical form. In case of defective matrices indications of the most appropriately computed canonical form. In case of defective matrices indication of the most appropriately computed canonical form are given.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제23권3호
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• pp.267-282
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• 2019

This paper examines how one can build a block tridiagonal structure for k-almost normal matrices and also for k-almost conjugate normal matrices. We shall see that these representations are created by unitary similarity and unitary congruance transformations, respectively. It shall be proven that the orders of diagonal blocks are 1, k + 2, 2k + 3, ${\ldots}$, in both cases. Then these block tridiagonal structures shall be reviewed for the cases where the mentioned matrices satisfy in a second-degree polynomial. Finally, for these processes, algorithms are presented.

• Journal of Information Science Theory and Practice
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• 제8권2호
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• pp.6-17
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• 2020

Word similarity is often measured to enhance system performance in the information retrieval field and other related areas. This paper reports on an experimental comparison of values for word similarity measures that were computed based on 50 intentionally selected words from a Reuters corpus. There were three targets, including (1) co-occurrence-based similarity measures (for which a co-occurrence frequency is counted as the number of documents or sentences), (2) context-based distributional similarity measures obtained from a latent Dirichlet allocation (LDA), nonnegative matrix factorization (NMF), and Word2Vec algorithm, and (3) similarity measures computed from the tf-idf weights of each word according to a vector space model (VSM). Here, a Pearson correlation coefficient for a pair of VSM-based similarity measures and co-occurrence-based similarity measures according to the number of documents was highest. Group-average agglomerative hierarchical clustering was also applied to similarity matrices computed by individual measures. An evaluation of the cluster sets according to an answer set revealed that VSM- and LDA-based similarity measures performed best.