• Title/Summary/Keyword: 유사 척도

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Comparative Study on the Measures of Similarity for the Location Template Matching (LTM) Method (Location Template Matching(LTM) 방법에 사용되는 유사성 척도들의 비교 연구)

  • Shin, Kihong
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2014.04a
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    • pp.506-511
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    • 2014
  • The location template matching (LTM) method is a technique of identifying an impact location on a structure, and requires a certain measure of similarity between two time signals. In general, the correlation coefficient is widely used as the measure of similarity, while the group delay based method is recently proposed to improve the accuracy of the impact localization. Another possible measure is the frequency response assurance criterion (FRAC), though this has not been applied yet. In this paper, these three different measures of similarity are examined comparatively by using experimental data in order to understand the properties of these measures of similarity. The comparative study shows that the correlation coefficient and the FRAC give almost the same information while the group delay based method gives the shape oriented information that is best suitable for the location template matching method.

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A Study on Words Representing Human Visual Sensibility in Residential Environment (주거환경이 시각적 감성어휘)

  • 윤정선;신미경;이강의;구아현
    • Science of Emotion and Sensibility
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    • v.3 no.2
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    • pp.67-74
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    • 2000
  • 본 연구는 주거환경에 대한 시각 감성을 대표하는 어휘를 선발하기 위해 수행되었다. 어휘수집의 첫 단계에서는 주거환경 중 시각 환경에 대한 감성을 표현하는 어휘 235개를 수집하였다. 두 번째 단계에서는 수집된 어휘를 다른 피험자들에게 제시하여 주거 환경의 분위기를 나타내는 어휘 로서 적절함의 정도를 7점 척도로 표시하도록 하여 매우 적절하다고 판단된 24개의 어휘를 선발하였다. 세 번째 단계에서는 이들 어휘를 무선 적으로 두 개씩 짝을 지어 두 단어가 유사한 정도를 7점 척도로 평가하도록 하였다. 이 설문으로부터 나온 데이터에 대해 요인분석, 군집분석, 다차원분석을 실시하여 시각적 주거환경에 대한 9개의 감성어휘를 추출하였다. 이와 함께 최종 단계에서 연구자들이 400여장의 실물 사진 열람을 통해 추출된 9개의 감성 어휘가 실제 시각적 주거환경을 나타내는 데에 적함한지를 다시 한번 검증하여 다음과 같은 10개의 어휘를 선발하였다. ‘안락한’, ‘개방적인’, ‘세련된’, ‘경쾌한’, ‘개성적인’, ‘단순한’, ‘화려한’, ‘중후한’, ‘고풍스로운’, ‘전원적인’.

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Object Segment Grouping for Wireless Mobile Streaming Media Services (무선 모바일 스트리밍 미디어 서비스를 위한 객체 세그먼트 그룹화)

  • Lee, Chong-Deuk
    • Journal of Digital Convergence
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    • v.10 no.4
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    • pp.199-206
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    • 2012
  • Increment of mobile client's information request in wireless mobile networks requires a new method to manage and serve the streaming media object. This paper proposes a new object segment grouping method for enhancing the performance of streaming media services in wireless mobile networks. The proposed method performs the similarity metric for the partitioned object segments, and it process the disjunction, conjunction, and filtering for these metrics. This paper was to decided the partitioned group of object segments for these operation metrics, and it decided the performance of streaming media services. The simulation result showed that the proposed method has better performance in throughput, average startup latency, and cache hit ratio.

A Study on the Measurement of the system effectiveness with ranked results (순위화시스템의 효과측정척도에 관한 연구)

  • 노정순
    • Journal of the Korean Society for information Management
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    • v.17 no.4
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    • pp.67-81
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    • 2000
  • This study discussed why Precision(& Recall) is not a good effectiveness measurement of IR system providing ranked results, reviewed other effectiveness measurements appropriate for ranked results, and proposed new measurements based on the average rank of relevant documents retrieved. The 18 case-sets of ranked results were used for evaluating 10 effectiveness measurements including proposed measurements. Simple measurements were significantly similar with the 11-Point Precision requiring complicated calculation.

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A Method Finding Representative Questionare for Mutual Information and Entropy (상호정보와 엔트로피를 활용한 대표문항 선택방법)

  • Choi, Byong-Su;Kim, Hyun-Ji
    • Communications for Statistical Applications and Methods
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    • v.17 no.4
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    • pp.591-598
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    • 2010
  • A questionnaire may consist of duplicated or similar items. This study finds the duplicated or similar items by using the MDS and the cluster analysis of response patterns. By identifying the characteristics of the cluster, those items are combined into a representative item. The similarity of items is measured by the mutual information.

A study on the efficiency of multidimensional scalin using bootstrap method (붓스트랩을 이용한 다차원척도법의 효율성 연구)

  • Kim, Woo-Jong;Kang, Kee-Hoon
    • Journal of the Korean Data and Information Science Society
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    • v.20 no.2
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    • pp.301-309
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    • 2009
  • Multidimensional scaling(MDS) is a statistical multivariate analysis technique that is often used in information visualization for exploring similarities or dissimilarities in data. In order to analyse and visualize data, MDS measures the dissimilarities between objects and uses them or their mean if they are repeatedly measured. When there exist outliers or when the variation of data is too large, we can hardly get reliable results on the research using MDS. In this paper, we consider the MDS based on bootstrap method when the variation of data is large. Standardized residual sum of squares is considered as measuring goodness-of-fit of the model. A real data analysis is include to examine our approach.

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A Rank-based Similarity Measure for Collaborative Filtering Systems (협력 필터링 시스템을 위한 순위 기반의 유사도 척도)

  • Lee, Soo-Jung
    • The Journal of Korean Association of Computer Education
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    • v.14 no.5
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    • pp.97-104
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    • 2011
  • Collaborative filtering is a methodology to recommend websites by obtaining data and opinions from the other users with similar tastes. During the past few years, this method has been used in various fields such as books, food, and movies in e-commerce systems. This study addresses the computation of similarity between users to determine items to be recommended in collaborative filtering systems. Previous studies measured similarity between users by treating each user's ratings independently without considering the distribution of the user's ratings. In contrast, this study measures similarity by utilizing position and rank information of each rating in the range of the user's ratings. The result of the experiments on the real datasets demonstrated that the proposed method improves the mean absolute error significantly, compared to the previous methods, especially when the predetermined range of ratings is large.

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Web-based Product Recommendation System with Probability Similarity Measure (확률 유사성척도를 활용한 웹 기반의 상품추천시스템)

  • Choi, Sang-Hyun;Ahn, Byeong-Seok
    • Journal of Intelligence and Information Systems
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    • v.13 no.1
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    • pp.91-105
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    • 2007
  • This research suggests a recommendation system that enables bidirectional communications between the user and system using a utility range-based product recommendation algorithm in order to provide more dynamic and personalized recommendations. The main idea of the proposed algorithm is to find the utility ranges of products based on user specified preference information and calculate the similarity by using overlapping probability of two range values. Based on the probability, we determine what products are similar to each other among the products in the product list of collaborative companies. We have also developed a Web-based application system to recommend similar products to the customer. Using the system, we carry out the experiments for the performance evaluation of the procedure. The experimental study shows that the utility range-based approach is a viable solution to the similar product recommendation problems from the viewpoint of both accuracy and satisfaction rate.

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