• Title/Summary/Keyword: Similarity evaluation

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Similarity Evaluation between Graphs: A Formal Concept Analysis Approach

  • Hao, Fei;Sim, Dae-Soo;Park, Doo-Soon;Seo, Hyung-Seok
    • Journal of Information Processing Systems
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    • v.13 no.5
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    • pp.1158-1167
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    • 2017
  • Many real-world applications information are organized and represented with graph structure which is often used for representing various ubiquitous networks, such as World Wide Web, social networks, and protein-protein interactive networks. In particular, similarity evaluation between graphs is a challenging issue in many fields such as graph searching, pattern discovery, neuroscience, chemical compounds exploration and so forth. There exist some algorithms which are based on vertices or edges properties, are proposed for addressing this issue. However, these algorithms do not take both vertices and edges similarities into account. Towards this end, this paper pioneers a novel approach for similarity evaluation between graphs based on formal concept analysis. The feature of this approach is able to characterize the relationships between nodes and further reveal the similarity between graphs. Therefore, the highlight of our approach is to take vertices and edges into account simultaneously. The proposed algorithm is evaluated using a case study for validating the effectiveness of the proposed approach on detecting and measuring the similarity between graphs.

Similarity Evaluation on Images of Textile Print Design for Digital Library (Digital Library를 위한 텍스타일 프린트 디자인의 이미지 유사성 평가)

  • Lee, Chae-Jung;Kim, Joo-Yong
    • Science of Emotion and Sensibility
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    • v.10 no.4
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    • pp.631-637
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    • 2007
  • This research focuses on similarity evaluation of images according to tones of images. Color space of images were converted RGB color space into HSI color space. The information entropy criteria has been taken for evaluating similarity of images for digital library. The similarity was then calculated by combining correlation coefficients and information entropy. Those two values are further analyzed with a relation to human sensibility.

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Air Similarity Test for the Evaluation of Aerodynamic Performance of Steam Turbine (스팀터빈의 공력성능 평가를 위한 공기 상사실험)

  • Lim, Byeung-Jun;Lee, Eun-Seok;Lee, Ik-Hyoung;Kim, Young-Sang;Kwon, Gee-Bum
    • 유체기계공업학회:학술대회논문집
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    • 2003.12a
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    • pp.73-79
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    • 2003
  • The steam turbine efficiency is an important factor in power plant. Accurate evaluation of steam turbine performance is essential. However, it is not easy to evaluate the steam turbine performance due to its high temperature and high pressure circumstance. Therefore most steam turbine performance tests were conducted by air similarity test. This paper described a test program for air similarity test of steam turbine at Korea Aerospace Research Institute. A test facility has been designed and built to evaluate aerodynamic performance of turbines. The test facility consists of air supply system, single stage test section, power absorption system, instrumentation and auxiliary system. For evaluation of steam turbine performance, the test of single stage axial turbine air similarity performance was conducted and uncertainty analysis was performed.

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A Tree-Compare Algorithm for Similarity Evaluation (유사도 평가를 위한 트리 비교 알고리즘)

  • Kim, Young-Chul;Yoo, Chae-Woo
    • The KIPS Transactions:PartA
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    • v.11A no.2
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    • pp.159-164
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    • 2004
  • In the previous researches, tree comparison methods are almost studied in comparing weighted or labeled tree(decorated tree). But in this paper, we propose a tree comparison and similarity evaluation algorithm can be applied to comparison of two normal trees. The algorithm converts two trees into node string using unparser, evaluates similarity and finally return similarity value from 0.0 to 1.0. In the experiment part of this paper, we visually presented matched nodes and unmatched nodes between two trees. By using this tree similarity algorithm, we can not only evaluate similarity between two specific programs or documents but also detect duplicated code.

Similarity Criteria in GUI and Icon Design - with an Emphasis on the Quantitative Evaluation using Checklists - (화상디자인의 유사성 판단기준에 대한 연구 - 체크리스트를 활용한 정량적인 평가 방법을 중심으로-)

  • 김소영;최민영;임창영
    • Archives of design research
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    • v.16 no.4
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    • pp.101-110
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    • 2003
  • This paper is focused on the similarity of GUI design and proposes checklists for evaluating similarity of GUI design in quantitative way and more important factors in this checklists. On the first, consideration of similarity and analysis of GUI properties are made, and from these results, the categories that affect the evaluation of similarity are extracted. The categories are consisted of 5 factors, which are concept, shape, color, relation, and multimedia. The checklists from above 5 categories are tested in 3-stage, and in this paper, 11 checklists from shape, color, and relation factor of the second stage are verified by online survey. The purpose of this survey is to find out the difference between user groups(designer, computer related, etc) and more important factors in the checklists that affect the total results of similarity. In the results of survey, the checklists have no relation with the user groups and among the checklists, external shape, composition element, and design methods have impact factors on the evaluation of similarity.

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Evaluation of Similarity Analysis of Newspaper Article Using Natural Language Processing

  • Ayako Ohshiro;Takeo Okazaki;Takashi Kano;Shinichiro Ueda
    • International Journal of Computer Science & Network Security
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    • v.24 no.6
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    • pp.1-7
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    • 2024
  • Comparing text features involves evaluating the "similarity" between texts. It is crucial to use appropriate similarity measures when comparing similarities. This study utilized various techniques to assess the similarities between newspaper articles, including deep learning and a previously proposed method: a combination of Pointwise Mutual Information (PMI) and Word Pair Matching (WPM), denoted as PMI+WPM. For performance comparison, law data from medical research in Japan were utilized as validation data in evaluating the PMI+WPM method. The distribution of similarities in text data varies depending on the evaluation technique and genre, as revealed by the comparative analysis. For newspaper data, non-deep learning methods demonstrated better similarity evaluation accuracy than deep learning methods. Additionally, evaluating similarities in law data is more challenging than in newspaper articles. Despite deep learning being the prevalent method for evaluating textual similarities, this study demonstrates that non-deep learning methods can be effective regarding Japanese-based texts.

Effects of Temporal Distance on Brand Extension Evaluation: Applying the Construal-Level Perspective to Brand Extensions

  • Park, Kiwan
    • Asia Marketing Journal
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    • v.17 no.1
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    • pp.97-121
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    • 2015
  • In this research, we examine whether and why temporal distance influences evaluations of two different types of brand extensions: concept-based extensions, defined as extensions primarily based on the importance or relevance of brand concepts to extension products; and similarity-based extensions, defined as extensions primarily based on the amount of feature similarity at the product-category level. In Study 1, we test the hypothesis that concept-based extensions are evaluated more favorably when they are framed to launch in the distant rather than in the near future, whereas similaritybased extensions are evaluated more favorably when they are framed to launch in the near rather than in the distant future. In Study 2, we confirm that this time-dependent differential evaluation is driven by the difference in construal level between the bases of the two types of extensions - i.e., brand-concept consistency and product-category feature similarity. As such, we find that conceptbased extensions are evaluated more favorably under the abstract than concrete mindset, whereas similarity-based extensions are evaluated more favorably under the concrete than abstract mindset. In Study 3, we extend to the case for a broad brand (i.e., brands that market products across multiple categories), finding that making accessible a specific product category of a broad parent brand influences evaluations of near-future, but not distant-future, brand extensions. Combined together, our findings suggest that temporal distance influences brand extension evaluation through its effect on the importance placed on brand concepts and feature similarity. That is, consumers rely on different bases to evaluate brand extensions, depending on their perception of when the extensions take place and on under what mindset they are placed. This research makes theoretical contributions to the brand extension research by identifying one important determinant to brand extension evaluation and also uncovering its underlying dynamics. It also contributes to expanding the scope of the construal level theory by putting forth a novel interpretation of two bases of perceived fit in terms of construal level. Marketers who are about to launch and advertise brand extensions may benefit by considering temporal-distance information in determining what content to deliver about extensions in their communication efforts. Conceptual relation of a parent brand to extensions needs to be emphasized in the distant future, whereas feature similarity should be highlighted in the near future.

A Definition of Similarity Measuring Function using Beauty Evaluation Extraction Factor of the Consonant (자음의 미적 평가 추출 요소를 이용한 유사도 함수 정의)

  • Han, Kun-Hee;Back, Soon-Hwa;Baek, Seung-Ho;Jun, Byoung-Min
    • Journal of the Korean Society of Industry Convergence
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    • v.3 no.3
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    • pp.229-236
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    • 2000
  • This paper proposes on the Hanguel character CAI system using image processing. For this, firstly, the characters written by elementary school students or foreigners arc captured by CCD camera. Secondly, Recognition is accomplished by pre-processing, thinning and recognition processes. Thirdly, strokes are separated and beauty evaluation is done by matching feature value of the input image from the similarity measure function. In particular, this paper describe to define the similarity measuring function using extracted factor values after getting the beauty evaluation factor values of the consonant in the entire CAI system. Finally, the effectiveness of the proposed system is demonstrated by experiments.

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Calculation of Objective Quality-Evaluation-Index for Mosaic Imagery (모자이크 영상의 객관적 품질평가지수 산정 방법)

  • Woo, Hee-Sook;Noh, Myoung-Jong;Park, June-Ku;Cho, Woo-Sug;Kim, Byung-Guk
    • Journal of Korean Society for Geospatial Information Science
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    • v.17 no.3
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    • pp.33-40
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    • 2009
  • This paper proposes the assessment method for objective quality-evaluation-index of mosaic images. Quality assessment was evaluated using seam-line method and similarity and contrast of adjacent images. The evaluation measure was calculated based on selected evaluation criteria and compared with human visual inspection. It was found that quantitative quality evaluation measure showed that the evaluation results were similar to human visual check. Conclusively experimental results proved that proposed evaluation measure could be used for quantitative and objective quality assessment of mosaic images.

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Grouping of Similar Programs using Program Similarity Evaluation (프로그램 유사도 평가를 이용한 유사 프로그램의 그룹 짓기)

  • 유재우;김영철
    • Journal of KIISE:Software and Applications
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    • v.31 no.1
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    • pp.82-88
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    • 2004
  • Comparing many programs like programming assignments one by one requires many costs. Moreover, if the checker would evaluate or grade assignments, much more time will be required. Even through the checker invest much time, fairness is not always guaranteed. These problems can be solved easily by grouping similar programs. So, programs after grouping can be easily evaluated and graded. In this paper, we propose and implement algerian performing grouping by similarity on many programs. The grouping algorithm evaluates similarity using algorithm proposed in (9), and performs a grouping following high similarity order. By using this grouping algorithm, the number of comparison among N programs can be reduced from N-1 times to N(N-1)/2 times. In the part of experiment and evaluation of this paper, we actually showed evaluation result by similarity using randomly 10 programming assignments at the university.