• Title/Summary/Keyword: 유사성 탐색

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Two-stage Content-based Image Retrieval Using the Dimensionality Condensation of Feature Vector (특징벡터의 차원축약 기법을 이용한 2단계 내용기반 이미지검색 시스템)

  • 조정원;최병욱
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.28 no.7C
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    • pp.719-725
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    • 2003
  • The content-based image retrieval system extracts features of color, shape and texture from raw images, and builds the database with those features in the indexing process. The search in the whole retrieval system is defined as a process which finds images that have large similarity to query image using the feature database. This paper proposes a new two-stage search method in the content-based image retrieval system. The method is that the features are condensed and stored by the property of Cauchy-Schwartz inequality in order to reduce the similarity computation time which takes a mostly response time from entering a query to getting retrieval results. By the extensive computer simulations, we have observed that the proposed two-stage search method successfully reduces the similarity computation time while maintaining the same retrieval relevance as the conventional exhaustive search method. We also have observed that the method is more effective as the number of images and dimensions of the feature space increase.

A Concept-based Semantic Network for Information Sharing in Multidatabase Systems (멀티데이터베이스 시스템에서 정보공유를 위한 개념-기반 의미망의 구축)

  • Lee, Jeong-Uk;Baek, Du-Gwon
    • Journal of KIISE:Databases
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    • v.28 no.2
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    • pp.188-203
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    • 2001
  • 멀티데이터베이스 시스템(multidatabase system)에서 여러 요소 데이터베이스(component database)에 대한 통합된 접근을 제공하기 위해서는 의미 이질성(semantic heterogeneity)이 탐색되고 해결되어져야 한다. 즉, 멀티데이터베이스 시스템은 각 요소 데이터베이스가 가지고 있는 정보의 의미를 이해하고 의미적으로 동등한 또는 유사한 정보들을 식별할 수 있어야 한다. 또한, 멀티데이터베이스 시스템은 사용자로 하여금 실세계의 동일한 정보를 가지고 있는 여러 다른 데이터베이스로부터 원하는 정보를 용이하게 획득할 수 있도록 해야 한다. 본 논문에서는, 요소 데이터베이스간의 의미 이질성을 탐색하고 해결하기 위하여 정보가 갖고 있는 개념간 의미관계에 기반한 의미망(semantic network)을 구축한다. 또한 의미질의어(semantic query language)를 제공하여 사용자가 스키마에 대한 사전 지식이 없이도 여로 자율적인 데이터베이스로부터 원하는 정보를 용이하게 획득 할 수 있도록 한다.

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Research on the Similarity of Furniture Design of Table Furniture in the Later Joseon Dynasty and Ming-style Furniture (조선시대 후기 가구와 명식(明式)가구 탁자(卓子)류 가구 조형 디자인의 유사성 연구)

  • Xiao, Yang;Kim, KieSu;Li, Yang
    • The Journal of the Korea Contents Association
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    • v.20 no.8
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    • pp.522-537
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    • 2020
  • The Joseon dynasty had close communication with the Ming and Qing dynasties on multiple levels. In the development process of furniture modeling design, the same cultural source and mutual communication, and the same factor was reflected in each other's furniture modeling. In this paper, "Furniture in the later Joseon Period" and "Ming style furniture" are taken as the research noumenon, table furniture as the specific research object, and from the perspective of "similarity" in the history of exchanges between the two countries, the overall modeling design and the local modeling design are selected to discuss the modeling design of traditional furniture in the two countries. In the analysis of specific research cases, there are similar genes in the overall modeling design of table furniture such as soban, warp bed and inkstone bed in the later Joseon Dynasty and table furniture such as kang, square table, wine table and incense table in the Ming and qing dynasties. In terms of local modeling, the appearance of similar desktop, cloud horn, leg, foot and other modeling designs better confirms the similarity in modeling design between the two countries. In this paper for "type of air hole" formative source speculated that traditional furniture is for Korean peninsula a tentative study of cultural studies. Considering the fact that the exchanges between Korea and China are expanding in many aspects, exploring the similarities in the traditional furniture will help to analyze the cultural exchanges between the two countries and promote the exchanges.

An Index Interpolation-based Subsequence Matching Algorithm supporting Normalization Transform in Time-Series Databases (시계열 데이터베이스에서 인덱스 보간법을 기반으로 정규화 변환을 지원하는 서브시퀀스 매칭 알고리즘)

  • No, Ung-Gi;Kim, Sang-Uk;Hwang, Gyu-Yeong
    • Journal of KIISE:Databases
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    • v.28 no.2
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    • pp.217-232
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    • 2001
  • 본 논문에서는 시계열 데이터베이스에서 정규화 변환을 지원하는 서브시퀀스 매칭 알고리즘을 제안한다. 정규화 변환을 시계열 데이터 간의 절대적인 유클리드 거리에 관계 없이, 구성하는 값들의 상대적인 변화 추이가 유사한 패턴을 갖는 시계열 데이터를 검색하는 데에 유용하다. 기존의 서브시퀀스 매칭 알고리즘을 확장 없이 정규화 변환 서브시퀀스 매칭에 단순히 응용할 경우, 질의 결과로 반환되어야 할 서부시퀀스를 모두 찾아내지 못하는 착오 기각이 발생한다. 또한, 정규화 변환을 지원하는 기존의 전체 매칭 알고리즘의 경우, 모든 가능한 질의 시퀀스 길이 각각에 대하여 하나씩의 인덱스를 생성하여야 하므로, 저장 공간 및 데이터 시퀀스 삽입/삭제의 부담이 매우 심각하다. 본 논문에서는 인덱스 보간법을 이용하여 문제를 해결한다. 인덱스 보간법은 인덱스가 요구되는 모든 경우 중에서 적당한 간격의 일부에 대해서만 생성된 인덱스를 이용하며, 인덱스가 필요한 모든 경우에 대한 탐색을 수행하는 기법이다. 제안된 알고리즘은 몇 개의 질의 시퀀스 길이에 대해서만 각각 인덱스를 생성한 후, 이를 이용하여 모든 가능한 길이의 질의 시퀀스에 대해서 탐색을 수행한다. 이때, 착오 기각이 발생하지 않음을 증명한다. 제안된 알고리즘은 질의 시에 주어진 질의 시퀀스의 길이에 따라 생성되어 있는 인덱스 중에서 가장 적절한 것을 선택하여 탐색을 수행한다. 이때, 생성되어 있는 인덱스의 개수가 많을수록 탐색 성능이 향상된다. 필요에 따라 인덱스의 개수를 변화함으로써 탐색 성능과 저장 공간 간의 비율을 유연하게 조정할 수 있다. 질의 시퀀스의 길이 256 ~ 512중 다섯 개의 길이에 대해 인덱스를 생성하여 실험한 결과, 탐색 결과 선택률이 $10^{-2}$일 때 제안된 알고리즘의 탐색 성능이 순차 검색에 비하여 평균 2.40배, 선택률이 $10^{-5}$일 때 평균 14.6배 개선되었다. 제안된 알고리즘의 탐색 성능은 탐색 결과 선택률이 작아질수록 더욱 향상되므로, 실제 데이터베이스 응용에서의 효용성이 높다고 판단된다.

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Study on the Similarity Functions for Image Compression (영상 압축을 위한 유사성 함수 연구)

  • Joo, Woo-Seok;Kang, Jong-Oh
    • The Transactions of the Korea Information Processing Society
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    • v.4 no.8
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    • pp.2133-2142
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    • 1997
  • Compared with previous compression methods, fractal image compression drastically increases compression rate by using block-based encoding. Although decompression can be done in real time even with softwares, the most serious problem in utilizing the fractal method is the time required for the encoding. In this paper, we propose and verify i) an algorithm that reduces the encoding time by reducing the number of similarity searching on the basis of dimensional informations, and ii) an algorithm that enhances the quality of the restored image on the basis of brightness and contrast information. Finally, a method that enables fast compression with little quality degradation is proposed.

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Exploration and functional expression of homologous lipases of Candida antarctica lipase B (Candida antarctica lipase B의 상동체 효소 탐색과 발현)

  • Park, Seongsoon
    • Korean Journal of Microbiology
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    • v.51 no.3
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    • pp.187-193
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    • 2015
  • Candida (also known as Pseudozyma) antarctica lipase B (CAL-B) has been intensely studied in academic and industrial fields. However, the research related to its homologous enzymes has been rarely reported. In the current investigation, protein sequence similarity search of CAL-B has been conducted and six homologous protein sequences were identified. After the syntheses of their codon-optimized genes, the synthetic genes have been cloned into a periplasmic expression vector to express in Escherichia coli. Among six homologous sequences, four sequences were successfully expressed in E. coli. The hydrolytic activities of the expressed proteins towards 4-nitrophenyl acetate and 4-nitrophenyl butyrate were measured and compared with those of CAL-B to identify whether the expressed proteins work as a hydrolase. It has been revealed that the expressed proteins can hydrolyze the substrates and the specific activities were determined as $(1.3-30){\times}10^{-2}{\mu}mol/min/mg$, which are lower than those of CAL-B. Among these homologous enzymes, Pseudozyma hubeiensis SY62 exhibits the comparable enantioselectivity to that of CAL-B towards the hydrolysis of (${\pm}$)-1-phenylethyl acetate.

CS-Tree : Cell-based Signature Index Structure for Similarity Search in High-Dimensional Data (CS-트리 : 고차원 데이터의 유사성 검색을 위한 셀-기반 시그니쳐 색인 구조)

  • Song, Gwang-Taek;Jang, Jae-U
    • The KIPS Transactions:PartD
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    • v.8D no.4
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    • pp.305-312
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    • 2001
  • Recently, high-dimensional index structures have been required for similarity search in such database applications s multimedia database and data warehousing. In this paper, we propose a new cell-based signature tree, called CS-tree, which supports efficient storage and retrieval on high-dimensional feature vectors. The proposed CS-tree partitions a high-dimensional feature space into a group of cells and represents a feature vector as its corresponding cell signature. By using cell signatures rather than real feature vectors, it is possible to reduce the height of our CS-tree, leading to efficient retrieval performance. In addition, we present a similarity search algorithm for efficiently pruning the search space based on cells. Finally, we compare the performance of our CS-tree with that of the X-tree being considered as an efficient high-dimensional index structure, in terms of insertion time, retrieval time for a k-nearest neighbor query, and storage overhead. It is shown from experimental results that our CS-tree is better on retrieval performance than the X-tree.

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A Study on the Application of Topic Modeling for the Book Report Text (독후감 텍스트의 토픽모델링 적용에 관한 탐색적 연구)

  • Lee, Soo-Sang
    • Journal of Korean Library and Information Science Society
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    • v.47 no.4
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    • pp.1-18
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    • 2016
  • The purpose of this study is to explore application of topic modeling for topic analysis of book report. Topic modeling can be understood as one method of topic analysis. This analysis was conducted with texts in 23 book reports using LDA function of the "topicmodels" package provided by R. According to the result of topic modeling, 16 topics were extracted. The topic network was constructed by the relation between the topics and keywords, and the book report network was constructed by the relation between book report cases and topics. Next, Centrality analysis was conducted targeting the topic network and book report network. The result of this study is following these. First, 16 topics are shown as network which has one component. In other words, 16 topics are interrelated. Second, book report was divided into 2 groups, book reports with high centrality and book reports with low centrality. The former group has similarities with others, the latter group has differences with others in aspect of the topics of book reports. The result of topic modeling is useful to identify book reports' topics combining with network analysis.

Development of new agrochemicals by quantitative structure-activity relationship (QSAR) methodology. III. 3D QSAR methodologies and computer-assisted molecular design (CAMD) (정량적인 구조-활성상관 (QSAR) 기법에 의한 새로운 농약의 개발. III. 3D QSAR 기법들과 컴퓨터를 이용한 분자설계(CAMD))

  • Sung, Nack-Do
    • The Korean Journal of Pesticide Science
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    • v.7 no.1
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    • pp.1-11
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    • 2003
  • Acoording to improvement of HTOS (high throughput organic synthesis) and HTS (high throughput screening) technique, the CoMFA (comparative molecular field analysis), CoMSIA (comparative molecular similarity indeces analysis) and molecular HQSAR (hologram quantitative structure-activity relationship) analysis techniques as methodology of computer assisted molecular design (CAMD) were introduced generally and summarized for some application cases.

Dynamic Recommendation System Using Web Document Type and Document Similarity in Cluster (웹 문서 형식과 클러스터 내의 문서 유사도를 이용한 동적 추천 시스템)

  • 김진수;김태용;이정현
    • Proceedings of the Korean Information Science Society Conference
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    • 2001.04b
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    • pp.274-276
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    • 2001
  • 기존의 여러 동적 추천 시스템에서 사용자들의 브라우징 패턴을 반영하려고 노력하였다 .그러나 대부분의 동적 추천 시스템들은 웹 문서들의 형식이나 웹 문서들 간의 연관성을 고려하지 않고, 사용자들의 브라우징 패턴에만 근거하기 때문에 연관성이 없거나 의미 없는 웹 문서들에 대한 추천까지 제공하는 문제점을 지니고 있다. 본 논문에서는 웹 문서들 사이의 유사도와 로그 파일 안에 들어있는 사용자들이 패턴을 이용하여 웹 문서 자체의 형식에 따라 연관된 웹 문서뿐만 아니라 순차적인 특성을 가진 웹 문서를 추천 문서로 제공한다. 이때 추천 웹 문서의 형식이 탐색 페이지이면 사용자 브라우징 순차 패턴 DB 중에서 사용자들이 자주 항해하는 순차적인 특성을 갖는 웹 문서까지 제공하는 동적 추천 시스템을 제안한다.

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