• Title/Summary/Keyword: Metric-Weighting

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An In-depth Study on Applying Metric Weighting to Space Syntax (공간구문론에의 거리가중개념 적용에 관한 심층 연구)

  • Kim, Minseok;Piao, Gensong
    • Journal of the Architectural Institute of Korea Planning & Design
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    • v.34 no.12
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    • pp.49-54
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    • 2018
  • Applying metric(distance) factor as weighting to spatial syntax is known to not contribute to the explanatory power for the human movement behavior as compared to the geometric(angle) factor according to the negative results of several related studies. However, Kim & Piao (2017) assumed that there is not a problem of the metric factor itself but a problem of the way of applying the metric factor as weighting, and presented a new possibility of the metric factor as weighting by proposing and verifying the methods of applying the metric weighting, which are different from the existing ones. The purpose of this study is to propose advanced methods of applying the metric weighting to space syntax, and to verify whether they contribute to the improvement of explanatory power of space syntax analysis. In this paper, we propose functions for combined depth of distance-step that combine the distance-weighted depth function with the step depth function and apply them to axial segment analysis to check the improvement of explanatory power of them.

A Feature Re-weighting Approach for the Non-Metric Feature Space (가변적인 길이의 특성 정보를 지원하는 특성 가중치 조정 기법)

  • Lee Robert-Samuel;Kim Sang-Hee;Park Ho-Hyun;Lee Seok-Lyong;Chung Chin-Wan
    • Journal of KIISE:Databases
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    • v.33 no.4
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    • pp.372-383
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    • 2006
  • Among the approaches to image database management, content-based image retrieval (CBIR) is viewed as having the best support for effective searching and browsing of large digital image libraries. Typical CBIR systems allow a user to provide a query image, from which low-level features are extracted and used to find 'similar' images in a database. However, there exists the semantic gap between human visual perception and low-level representations. An effective methodology for overcoming this semantic gap involves relevance feedback to perform feature re-weighting. Current approaches to feature re-weighting require the number of components for a feature representation to be the same for every image in consideration. Following this assumption, they map each component to an axis in the n-dimensional space, which we call the metric space; likewise the feature representation is stored in a fixed-length vector. However, with the emergence of features that do not have a fixed number of components in their representation, existing feature re-weighting approaches are invalidated. In this paper we propose a feature re-weighting technique that supports features regardless of whether or not they can be mapped into a metric space. Our approach analyses the feature distances calculated between the query image and the images in the database. Two-sided confidence intervals are used with the distances to obtain the information for feature re-weighting. There is no restriction on how the distances are calculated for each feature. This provides freedom for how feature representations are structured, i.e. there is no requirement for features to be represented in fixed-length vectors or metric space. Our experimental results show the effectiveness of our approach and in a comparison with other work, we can see how it outperforms previous work.

Improved Collaborative Filtering Using Entropy Weighting

  • Kwon, Hyeong-Joon
    • International Journal of Advanced Culture Technology
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    • v.1 no.2
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    • pp.1-6
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    • 2013
  • In this paper, we evaluate performance of existing similarity measurement metric and propose a novel method using user's preferences information entropy to reduce MAE in memory-based collaborative recommender systems. The proposed method applies a similarity of individual inclination to traditional similarity measurement methods. We experiment on various similarity metrics under different conditions, which include an amount of data and significance weighting from n/10 to n/60, to verify the proposed method. As a result, we confirm the proposed method is robust and efficient from the viewpoint of a sparse data set, applying existing various similarity measurement methods and Significance Weighting.

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New Weighting Functions for the Modified CIELAB Colour-Difference Formulae (수정 CIELAB 색차식을 위한 새로운 색차 가중 함수)

  • Kim, Dong-Ho
    • Textile Coloration and Finishing
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    • v.9 no.6
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    • pp.51-57
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    • 1997
  • The lightness, chroma and hue tolerances with respect to the standard colour position in the CIELAB space have been studied in detail using the various existing data sets and the set form this study. The lightness tolerance showed a clear dependency upon the metric lightness for medium to light colour, but in the case of dark colours there was a discrepancy between the data sets. Both the chroma and hue tolerances showed dependency upon both the chroma and hue-angle and not the single dependency upon the metric chroma, as assumed in the CIE94 formula. New weighting functions were derived from the above experimental evidence, and finally a new formula, LCD(Leeds Colour Difference) was proposed. The LCD formula is nearly as simple and flexible as CIE94 but smoothes the individual weighting functions, especially for lightness tolerances for light colours and chromaticity discrimination near the blue region.

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Instance Based Learning Revisited: Feature Weighting and its Applications

  • Song Doo-Heon;Lee Chang-Hun
    • Journal of Korea Multimedia Society
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    • v.9 no.6
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    • pp.762-772
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    • 2006
  • Instance based learning algorithm is the best known lazy learner and has been successfully used in many areas such as pattern analysis, medical analysis, bioinformatics and internet applications. However, its feature weighting scheme is too naive that many other extensions are proposed. Our version of IB3 named as eXtended IBL (XIBL) improves feature weighting scheme by backward stepwise regression and its distance function by VDM family that avoids overestimating discrete valued attributes. Also, XIBL adopts leave-one-out as its noise filtering scheme. Experiments with common artificial domains show that XIBL is better than the original IBL in terms of accuracy and noise tolerance. XIBL is applied to two important applications - intrusion detection and spam mail filtering and the results are promising.

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Constructing relationships in a hierarchical file system

  • Yoon, Young-Woo
    • 한국HCI학회:학술대회논문집
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    • 2006.02a
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    • pp.902-908
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    • 2006
  • We propose a scheme for more efficient navigation in a hierarchical file system. In the proposed scheme, a program running in the background computes the degree of relationship between a current file and others, and builds a list of the most related files. The current relationship metric being used by the program is a linear combination of five parameters: the name, the directory path, the type, the created time, and the last accessed time of a file. A simulated annealing algorithm is used in order to determine the weighting factors of the parameters. A set of experiments were conducted in order to access the effectiveness of the proposed scheme.

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A Usability Assessment Metric for Ubiquitous Services: Quantification of the Interactivity Attribute in Inter-personal Services

  • Lee, Joo-Hwan;Song, Joo-Bong;Yun, Myung-Hwan
    • Journal of the Ergonomics Society of Korea
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    • v.31 no.1
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    • pp.63-76
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    • 2012
  • Objective: The main objective of this study is to propose a user-centered assessment metric for ubiquitous services. Background: As the ubiquitous era took off, the interactions between ubiquitous services and users have come to take an important position. It is essential to conceptualize a new assessment model that considers human-system interaction capability with a user-centered design perspective. Method: The evaluation model for the interactivity of ubiquitous service was approached from the concept of usability and inter-personality of services. As a validation study, suggested assessment metric was utilized to evaluate the u-Home service. Priority weighting of each assessment metric was derived using the quantification type-I analysis. Results: To evaluate interactivity, this study suggested a quantitative metric for user testing performed after classifying the interactivity characteristics to contextualization; ubiquity; user experience; and service capability. Conclusion: This study suggest the metric for the ubiquitous service that are experienced in real life, and introduced the concept of ubiquitous service interactivity. Application: The suggested evaluation metric can be used to evaluate interactivity level of ubiquitous service and identify the potential problem and usability requirements at the early stage of service development.

A Fine Granular Scalable Video Coding Algorithm using Frequency Weighting (주파수 특성을 이용한 미세 계위적 동영상 부호화 방법)

  • 김승환;호요성
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.40 no.6
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    • pp.124-131
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    • 2003
  • In this paper, we propose a Progressive scalable video coding algorithm using frequency weighting in the DCT domain. Since the human visual system (HVS) can be modeled as a nonlinear point transformation, called the modulation transfer function (MTF), we tan use the frequency weighting matrix to enhance the video image quality. We change this frequency weighting matrix into the frequency shift matrix to apply to the bit-plane coding method for the fine granular scalable (FGS) video coding We also define a new error metric JNDE (just noticeable difference) to measure the perceptual image quality in terms of human vision.

Quantification Methods for Software Entity Complexity with Hybrid Metrics (혼성 메트릭을 이용한 소프트웨어 개체 복잡도 정량화 기법)

  • Hong, Euii-Seok;Kim, Tae-Guun
    • The KIPS Transactions:PartD
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    • v.8D no.3
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    • pp.233-240
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    • 2001
  • As software technology is in progress and software quantification is getting more important, many metrics have been proposed to quantify a variety of system entities. These metrics can be classified into two different forms : scalar metric and metric vector. Though some recent studies pointed out the composition problem of the scalar metric form, many scalar metrics are successfully used in software development organizations due to their practical applications. In this paper, it is concluded that hybrid metric form weighting external complexity is most suitable for scalar metric form. With this concept, a general framework for hybrid metrics construction independent of the development methodologies and target system type is proposed. This framework was successfully used in two projects that quantify the analysis phase of the structured methodology and the design phase of the object oriented real-time system, respectively. Any organization can quantify system entities in a short time using this framework.

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Locating the damaged storey of a building using distance measures of low-order AR models

  • Xing, Zhenhua;Mita, Akira
    • Smart Structures and Systems
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    • v.6 no.9
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    • pp.991-1005
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    • 2010
  • The key to detecting damage to civil engineering structures is to find an effective damage indicator. The damage indicator should promptly reveal the location of the damage and accurately identify the state of the structure. We propose to use the distance measures of low-order AR models as a novel damage indicator. The AR model has been applied to parameterize dynamical responses, typically the acceleration response. The premise of this approach is that the distance between the models, fitting the dynamical responses from damaged and undamaged structures, may be correlated with the information about the damage, including its location and severity. Distance measures have been widely used in speech recognition. However, they have rarely been applied to civil engineering structures. This research attempts to improve on the distance measures that have been studied so far. The effect of varying the data length, number of parameters, and other factors was carefully studied.