• 제목/요약/키워드: Technology Similarity

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Global Sequence Homology Detection Using Word Conservation Probability

  • Yang, Jae-Seong;Kim, Dae-Kyum;Kim, Jin-Ho;Kim, Sang-Uk
    • Interdisciplinary Bio Central
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    • 제3권4호
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    • pp.14.1-14.9
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    • 2011
  • Protein homology detection is an important issue in comparative genomics. Because of the exponential growth of sequence databases, fast and efficient homology detection tools are urgently needed. Currently, for homology detection, sequence comparison methods using local alignment such as BLAST are generally used as they give a reasonable measure for sequence similarity. However, these methods have drawbacks in offering overall sequence similarity, especially in dealing with eukaryotic genomes that often contain many insertions and duplications on sequences. Also these methods do not provide the explicit models for speciation, thus it is difficult to interpret their similarity measure into homology detection. Here, we present a novel method based on Word Conservation Score (WCS) to address the current limitations of homology detection. Instead of counting each amino acid, we adopted the concept of 'Word' to compare sequences. WCS measures overall sequence similarity by comparing word contents, which is much faster than BLAST comparisons. Furthermore, evolutionary distance between homologous sequences could be measured by WCS. Therefore, we expect that sequence comparison with WCS is useful for the multiple-species-comparisons of large genomes. In the performance comparisons on protein structural classifications, our method showed a considerable improvement over BLAST. Our method found bigger micro-syntenic blocks which consist of orthologs with conserved gene order. By testing on various datasets, we showed that WCS gives faster and better overall similarity measure compared to BLAST.

워드 임베딩(Word Embedding)을 활용한 최적의 키워드 추출 및 검색 방법 연구 (A Study on the Optimal Search Keyword Extraction and Retrieval Technique Generation Using Word Embedding)

  • 이정인;안진희;고경택;김영석
    • 한국지반신소재학회논문집
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    • 제22권2호
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    • pp.47-54
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    • 2023
  • 본 논문에서는 자료 조사를 위한 최적의 키워드 추출 및 검색 방법을 제안하였으며, 북한 건설 관련 동향 파악을 예시로 제안 방법을 검증하였다. 대표적인 국내 언론 플랫폼인 빅카인즈(BigKinds)를 활용하여 표본 기사를 선정하고 키워드를 추출하였다. 추출된 키워드는 워드 임베딩(Word Embedding)을 활용하여 벡터화하였으며, 이를 토대로 코사인 유사도(Cosine Similarity)를 통해 추출된 키워드 간의 유사도를 검사하였다. 또한 상위 빈도수 10개에 대한 키워드를 기준으로 유사도 0.5 이상인 키워드들을 군집화하였다. 각 군집들은 빅카인즈 검색 양식에 맞추어 군집 내부 키워드 간에는 'OR', 군집 간에는 'AND'로 형성하였다. 심층 분석 결과, 본래 목적에 맞는 유의미한 기사들이 추출되었음을 확인할 수 있었다. 기존의 분류체계 및 검색 양식을 변형시키지 않은 상태에서 사용자의 세부 목적을 충족시키는 자료 조사·분류가 가능하게 되었다는 점에서 의의를 갖는다.

A Table Integration Technique Using Query Similarity Analysis

  • Choi, Go-Bong;Woo, Yong-Tae
    • 한국컴퓨터정보학회논문지
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    • 제24권3호
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    • pp.105-112
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    • 2019
  • In this paper, we propose a technique to analyze similarity between SQL queries and to assist integrating similar tables. First, the table information was extracted from the SQL queries through the query structure analyzer, and the similarity between the tables was measured using the Jacquard index technique. Then, similar table clusters are generated through hierarchical cluster analysis method and the co-occurence probability of the table used in the query is calculated. The possibility of integrating similar tables is classified by using the possibility of co-occurence of similarity table and table, and classifying them into an integrable cluster, a cluster requiring expert review, and a cluster with low integration possibility. This technique analyzes the SQL query in practice and analyse the possibility of table integration independent of the existing business, so that the existing schema can be effectively reconstructed without interruption of work or additional cost.

A Study on Extracting Car License Plate Numbers Using Image Segmentation Patterns

  • Jang, Eun-Gyeom
    • 한국컴퓨터정보학회논문지
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    • 제23권10호
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    • pp.87-94
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    • 2018
  • This paper proposes a method of detecting the license plates of vehicles. The proposed technology applicable to different formats of license plates detects the numbers by standardizing the images at edge points. Specifically, in accordance with the format of each license plate, the technology captures the image in the character segment, and compares it against the sample model to derive their similarity and identify the numbers. Characters with high similarities are used to form a group of candidates and to extract the final characters. Analyzing the experimental results found the similarity of the extracted characters exceeded 90%, whereas that of less identifiable numbers was markedly lower. Still, the accuracy of the extracted characters with the highest similarity was over 80%. The proposed technology is applicable to extracting the character patterns of certain formats in diverse and useful ways.

A Density Peak Clustering Algorithm Based on Information Bottleneck

  • Yongli Liu;Congcong Zhao;Hao Chao
    • Journal of Information Processing Systems
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    • 제19권6호
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    • pp.778-790
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    • 2023
  • Although density peak clustering can often easily yield excellent results, there is still room for improvement when dealing with complex, high-dimensional datasets. One of the main limitations of this algorithm is its reliance on geometric distance as the sole similarity measurement. To address this limitation, we draw inspiration from the information bottleneck theory, and propose a novel density peak clustering algorithm that incorporates this theory as a similarity measure. Specifically, our algorithm utilizes the joint probability distribution between data objects and feature information, and employs the loss of mutual information as the measurement standard. This approach not only eliminates the potential for subjective error in selecting similarity method, but also enhances performance on datasets with multiple centers and high dimensionality. To evaluate the effectiveness of our algorithm, we conducted experiments using ten carefully selected datasets and compared the results with three other algorithms. The experimental results demonstrate that our information bottleneck-based density peaks clustering (IBDPC) algorithm consistently achieves high levels of accuracy, highlighting its potential as a valuable tool for data clustering tasks.

R&D과제의 기술분류를 이용한 사업간 유사도 분석 기법에 관한 연구 (A study on Similarity analysis of National R&D Programs using R&D Project's technical classification)

  • 김주호;김영자;김종배
    • 디지털콘텐츠학회 논문지
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    • 제13권3호
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    • pp.317-324
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    • 2012
  • 최근 R&D 투자효율성 제고를 목표로 사업 간의 유사중복 조정에 대한 중요성이 강조되고 있으나, 과제 혹은 예산요구서 내용 등을 텍스트 기반으로 비교하는 기존 유사검색 방식은 내용의 품질 편차 등으로 인해 유의미한 유사성 도출에 제한점이 있다. 이러한 텍스트 기반의 키워드 추출을 통한 유사검색 한계성을 극복하기 위한 방안으로 본 연구에서는 사업 간 유사도 분석 시 과제의 기술분류를 활용한다. 국가R&D사업 조사 분석 시 수집된 과제들의 과학기술표준분류를 추출하여 사업별 고유벡터 모형을 생성 후 이를 이용하여 코사인 기반, 유클리디안 거리기반 알고리즘을 통해 각 사업 간 유사도를 측정하였으며 기존 키워드 추출방식으로 유사도를 측정한 결과와의 비교를 통해 연구 효율성을 검증하였다.

불응축가스가 평판위 응축열전달에 미치는 영향에 관한 연구 (A study on effect of heat transfer of condensation including noncondensable gas over a flat plate)

  • 양대일;정형호
    • Journal of Advanced Marine Engineering and Technology
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    • 제24권1호
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    • pp.25-30
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    • 2000
  • In present paper, mass transfer over a flat plate with film condensation including noncondesable gas is analyzed with the help of similarity methods. Couette flow was assumed in liquid film and boundary-layer approximation was used in the ambient flow. Governing equations were transformed into the ordinary differential equtions by the similarity methods. Runge-Kutta and shooting method were used in order to fine the effect of mass transfer on the velocity and concentrations at the liquid-vapor interface.

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Background Initialization by Spatiotemporal Similarity

  • 박구만
    • 방송공학회논문지
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    • 제12권3호
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    • pp.289-292
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    • 2007
  • A background initialization algorithm based on the spatiotemporal similarity measure in a motion tracking system is proposed. From the accumulated difference between the base frame and the other frames in a subinterval, the regions affected by moving objects are located. The median is applied over the subsequence in the subinterval in which co-located regions share the similarity. The outputs from each subinterval are filtered by second stage median filter. The proposed method showed good results even in the busy and crowded sequences where the real background does not exit.

Patent Document Similarity Based on Image Analysis Using the SIFT-Algorithm and OCR-Text

  • Park, Jeong Beom;Mandl, Thomas;Kim, Do Wan
    • International Journal of Contents
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    • 제13권4호
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    • pp.70-79
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    • 2017
  • Images are an important element in patents and many experts use images to analyze a patent or to check differences between patents. However, there is little research on image analysis for patents partly because image processing is an advanced technology and typically patent images consist of visual parts as well as of text and numbers. This study suggests two methods for using image processing; the Scale Invariant Feature Transform(SIFT) algorithm and Optical Character Recognition(OCR). The first method which works with SIFT uses image feature points. Through feature matching, it can be applied to calculate the similarity between documents containing these images. And in the second method, OCR is used to extract text from the images. By using numbers which are extracted from an image, it is possible to extract the corresponding related text within the text passages. Subsequently, document similarity can be calculated based on the extracted text. Through comparing the suggested methods and an existing method based only on text for calculating the similarity, the feasibility is achieved. Additionally, the correlation between both the similarity measures is low which shows that they capture different aspects of the patent content.

지역적 밝기 변화에 강인한 물체 인식을 위한 지역 서술자와 엔트로피 기반 유사도 척도에 관한 연구 (A study on a local descriptor and entropy-based similarity measure for object recognition system being robust to local illumination change)

  • 양정은;양승용;홍석근;조석제
    • Journal of Advanced Marine Engineering and Technology
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    • 제38권9호
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    • pp.1112-1118
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    • 2014
  • 본 논문에서는 지역적인 밝기 변화에 강인한 지역 서술자와 유사도 척도를 제안한다. 제안한 지역 서술자는 Haar 웨이블렛 필터를 이용하여 특징점과 주변의 주파수 특성을 포함한 지역 서술자를 정의하여 지역적으로 불균일한 조명의 영향에도 특징점을 명확히 서술할 수 있다. 제안한 유사도 척도는 기존의 엔트로피 기반의 유사도에 지역 서술자로 계산한 유사도를 결합한 형태이다. 이는 지역적인 조명의 변화가 발생한 영역의 유사도를 정확히 반영할 수 있다. 실험을 통해 제안한 방법의 성능을 검증하였다.