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The Discovery of Attribute Feature Cluster for Any Clustering Result Based on Outlier Detection Technique

The Discovery of Attribute Feature Cluster for Any Clusterin...

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International conference on Internet Computing in Science and Engineering (ICICSE)

作者： Gang Liu Jiming Pang Xiufeng Piao Shaobin Huang College of Computer Science and Technology Harbin Engineering of Technology Harbin Heilongjiang China College of Computer Science and Technology Jilin University Changchun Jilin China

The comprehension of the clustering result is a problem that hasn't yet resolve, which having important meaning to the usage of the cluster result and the evaluation of the cluster effect. We put forward the method discovering attribute feature cluster for any clustering result based on outlier detection technique, and put forward an outlier detection algorithm based on even distribution pattern. Through carrying on outlier analysis to all data cluster attribute descriptions, we discovered the feature attribute of each data cluster, and then carried out the comprehension to the clustering result. The remarkable point lies in the method doesn't only aim at a particular clustering algorithm, but also the analysis of any the clustering algorithm result. Experiment to the UCI data set indicated, the method submitted in this paper obtained better result.

关键词： Detection algorithms Clustering algorithms Algorithm design and analysis Educational institutions Computer science data analysis data visualization Multidimensional systems Internet Displays

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Application of keyword map to decision support through exploratory search

Application of keyword map to decision support through explo...

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IEEE International conference on Systems, Man and Cybernetics

作者： Tomoki Kajinmi Toshiyuki Ogasawara Jhoji Komiya Yasufumi Takama Information & Communications System Engineering Tokyo Metropolitan University Tokyo Japan Electronic Systems and Engineering Tokyo Metropolitan Institute of Technology Tokyo Japan

This paper examines users behavior in decision making through exploratory search on a keyword map. The keyword map is a kind of interactive information visualization system, which displays relationships between objects (keywords). The system has been studied for analyzing data. The keyword map has a multiple relevance controller for analyzing relationship between keywords, which is represented by multiple attributes, from various viewpoints. A user can adjust weights of attributes according to his/her interest, using the controller. We expect that the keyword map can support compensatory/non-compensatory decision strategies by the multiple relevance controller. We perform an experiment for confirming user's behavior during exploratory search on the keyword map. Experimental result shows a user operates flexibly the multiple relevance controller according to his/her decision strategies.

关键词： Decision making Systems engineering and theory Displays Weight control Springs data analysis Animation Bars data visualization Information retrieval

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Quantitative abdominal fat estimation using MRI

Quantitative abdominal fat estimation using MRI

引用

International conference on Pattern Recognition

作者： O. Dahlqvist Leinhard A. Johansson J. Rydell O. Smedby F. Nystrom P. Lundberg M. Borga Center for Medical Image Science and Visualization (CMIV) Linköping University Sweden Department of Biomedical Engineering Linkoping University Sweden Department of Medical and Health Sciences Linkoping University Sweden

ISBN: (纸本)9781424421749

This paper introduces a new method for automatic quantification of subcutaneous, visceral and non-visceral internal fat from MR-images acquired using the two point Dixon technique in the abdominal region. The method includes (1) a three dimensional phase unwrapping to provide water and fat images, (2) an image intensity inhomogeneity correction, and (3) a morphon based registration and segmentation of the tissue. This is followed by an integration of the corrected fat images within the different fat compartments that avoids the partial volume effects associated with traditional fat segmentation methods. The method was tested on 18 subjects before and after a period of fast-food hyper-alimentation showing high stability and performance in all analysis steps.

关键词： Abdomen Magnetic resonance imaging Image segmentation Biomedical imaging Biomedical engineering visualization Testing Stability analysis Performance analysis data acquisition

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Visualizing Classifier Performance on Different Domains

Visualizing Classifier Performance on Different Domains

引用

International conference on Tools for Artificial Intelligence (ICTAI)

作者： Rocio Alaiz-Rodríguez Nathalie Japkowicz Peter Tischer Dpto. de Ingeniería Eléctrica y de Sistemas Universidad de León Spain School of Information Technology and Engineering University of Ottawa Canada Clayton School of Information Technology Monash University Australia

Classifier performance evaluation typically gives rise to vast numbers of results that are difficult to interpret. On the one hand, a variety of different performance metrics can be applied; and on the other hand, evaluation must be conducted on multiple domains to get a clear view of the classifier's general behaviour. In this paper, we present a visualization technique that allows a user to study the results from a domain point of view and from a classifier point of view. We argue that classifier evaluation should be done on an exploratory basis. In particular, we suggest that, rather than pre-selecting a few metrics and domains to conduct our evaluation on, we should use as many metrics and domains as possible and mine the results of this study to draw valid and relevant knowledge about the behaviour of our algorithms. The technique presented in this paper will enable such a process.

关键词： Information technology Measurement data mining Artificial intelligence Machine learning algorithms Machine learning Algorithm design and analysis data visualization Performance analysis

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Orientation distribution estimation for Q-ball imaging

Orientation distribution estimation for Q-ball imaging

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IEEE Computer Society conference on Computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Yogesh Rathi Oleg Michailovich Sylvain Bouix M. E. Shenton Harvard Medical School Psychiatry Neuroimaging Laboratory Boston MA USA University of Waterloo of Canada Canada

We propose a novel fast and analytical method to obtain the orientation distribution function (ODF) from diffusion weighted signals measured using the Q-ball imaging methodology. Past work has involved using the spherical harmonics or radial basis functions to represent the ODF. In this work, we propose to use the hyperspherical de la Vallee Poussin kernel to represent the measured Q-ball signal and derive its spherical radon transform to analytically compute the corresponding ODF. To minimize the number of coefficients used to represent the resulting ODF, we use the matching pursuit algorithm. In particular, we show how to extract principal diffusion directions that are separated by as small as 22.5 degrees in orientation. We show, with experiments, the robustness of the proposed method to signal noise and compare it with ODF computation using spherical harmonics on some synthetic and real data set. The proposed method is particularly useful in applications like tractography, segmentation or for better visualization of principal diffusion directions.

关键词： Signal analysis Matching pursuit algorithms Image analysis Distribution functions Weight measurement Kernel Pursuit algorithms data mining Noise robustness data visualization

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Network P2P for Exploring and visualization of Proteomic data: Possibility of Handling data and Analysing Them under Different Perspectives

Network P2P for Exploring and Visualization of Proteomic Dat...

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International conference on Biocomputation, Bioinformatics, and Biomedical Technologies, BIOTECHNO

作者： G. Mercurio S. Maglio A. Agrusti G. De Nunzio R. Cataldo I. De Mitri M. Favetta A. Massafra G. Marsella D. Vergara M. Maffia A. Vasilateanu L. D. Serbanati Istituto Tecnologie Biomediche CNR Italy D. Scienza dei Materiali INFN-University of Salento Italy INFN-University of Salento Italy D. Ingegneria dell'Innovazione INFN-University of Salento Italy D. Scienze e Tecnologie Biologiche ed Ambientali University of Salerno Italy University Politehnica of Bucharest Romania

Our group has started a project aiming at the development of analysis algorithms devoted to images produced by two-dimensional electrophoresis (2-DE) for general applications in the field of proteomics. General analysis problems have been addressed, with the ultimate goal of the maximization of the "automation level" of the analysis procedure, without reducing the accuracy now reachable only with manual intervention. For this, the group is analyzing 2-DE images that are already stored or that will be produced by means of the instrumentation and the know-how of the biologists participating to the project. It's obvious that the "key" for the project success is primarily the availability of many images produced by different groups, but especially their "comparability", and their significant "clinical contextualization". For these reasons, the group has started the implementation of federation of heterogeneous bio banks of images founded on open Registry/Repository for P2P architecture (ebXML RR)[1], on images stored with standard metadata for their comparability (EFMI MIP) [2], and on standard electronic documents for their clinical contextualization (HL7 CDA) [3]. This paper summarizes the concepts of the initiative and describes possibility of handling data and analysing them under different perspectives.

关键词： data visualization Proteomics data analysis Proteins Algorithm design and analysis Image analysis Electrokinetics Automation Pathology Software tools

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Performance Comparison of Nonlinear Dimensionality Reduction Methods for Image data Using Different Distance Measures

Performance Comparison of Nonlinear Dimensionality Reduction...

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International conference on Computational Intelligence and Security

作者： Mudasser Naseer Shi-Yin Qin School of Automation Science and Electrical Engineering Beihang University Beijing China

ISBN: (纸本)9781424441969

During recent years a special class of nonlinear dimensionality reduction (NLDR) methods known as manifold learning methods, obtain a lot of attention for low dimension representation of high dimensional data. Most commonly used NLDR methods like Isomap, locally linear embedding, local tangent space alignment, Hessian locally linear embedding, Laplacian eigenmaps and diffusion maps, construct their logic on finding neighborhood points of every data point in high dimension space. These algorithms use Euclidean distance as measurement metric for distance between two data points. In literature different (dis)similarity measures are available for measuring distances between two data points/images. In this paper the authors made a systematic comparative analysis for performance of different NLDR algorithms in reducing high dimensional image data into a low dimensional 2D data using different distance measures. The performance of an algorithm is measured by the fact that how successfully it preserves intrinsic geometry of high dimensional manifold. visualization of low dimensional data reveals the original structure of high dimensional data.

关键词： Learning systems Independent component analysis Euclidean distance Principal component analysis Automation Laplace equations Image analysis Performance analysis Algorithm design and analysis Geometry

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Voyage analysis Applied to Geovisual Analytics

Voyage Analysis Applied to Geovisual Analytics

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International conference on Information Visualisation (IV)

作者： Patrik Lundblad Mikael Jern Camilla Forsell Visual Information Technology and Applications (VITA) Department of Science and Technology University of Linköping Norrkoping Sweden

This paper demonstrates the synergy of common InfoVis and GeoVis interaction techniques and the logistic application domain demonstrated in the customized visualize performance data (VISPER) application. In VISPER multi-dimensional, multi-source, time-varying and geospatial digital information from voyage analysis is represented to facilitate decision-making. Using common InfoVis components for multivariate data together with logistics visualization in a new synergy aids the users in their work examining ship and route performance. An evaluation of the usability was performed to gather insights for future development. The results from the evaluation show that the overall impression of VISPER was highly positive and participants enjoyed using it. Feedback obtained was highly valuable and directly applicable for improvements and further development.

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SDMA: A Service-based Architecture for data Mining Applications

SDMA: A Service-based Architecture for Data Mining Applicati...

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IEEE International conference on Services Computing (SCC)

作者： Liutong Xu Yi Wang Guanhui Geng Xiangang Zhao Nan Du Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia Beijing University of Posts and Telecommunications Beijing China

In the field of data mining, most of necessary resources, such as datasets, computing resources, might be distributed in different places of the world, which impedes scientists to do research successfully. Service science advocates every available resource as a service and focuses on their collaboration to settle a problem. Here, we propose a service-based architecture for data mining applications, including configuration service, service engine, monitor service, analysis service, visualization service, computing service and data & algorithm provision service. The first 5 services focus on 5 specific aspects of data mining requirements. A demo system has also been developed to validate the feasibility of our architecture.

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Impact analysis from Multiple Perspectives: Evaluation of Traceability Techniques

Impact Analysis from Multiple Perspectives: Evaluation of Tr...

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International conference on Software Engineering Advances (ICSEA)

作者： Salma Imtiaz Naveed Ikram Saima Imtiaz International Islamic University Islamabad Pakistan Muhammad Ali Jinnah University Islamabad Pakistan

Impact analysis is a core activity of requirement change management (RCM). The pre-requisite of impact analysis activity is traceability information. There are various techniques present in literature used for storing, extracting and updating the traceability information for the purpose of performing impact analysis. We have identified the need to perform impact analysis from multiple perspectives. The three perspectives present in literature namely technical, organizational and personal perspective; help in identifying technical, organizational and personal impacts. This paper evaluates various traceability techniques with respect to their usefulness for Multiple Perspective Impact analysis (MPIA).

关键词： Performance analysis Information analysis Information retrieval data mining IEC standards ISO standards Software engineering visualization Guidelines Performance evaluation

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