for Journals by Title or ISSN
for Articles by Keywords
help
  Subjects -> COMPUTER SCIENCE (Total: 2050 journals)
    - ANIMATION AND SIMULATION (30 journals)
    - ARTIFICIAL INTELLIGENCE (99 journals)
    - AUTOMATION AND ROBOTICS (100 journals)
    - CLOUD COMPUTING AND NETWORKS (64 journals)
    - COMPUTER ARCHITECTURE (9 journals)
    - COMPUTER ENGINEERING (10 journals)
    - COMPUTER GAMES (16 journals)
    - COMPUTER PROGRAMMING (27 journals)
    - COMPUTER SCIENCE (1196 journals)
    - COMPUTER SECURITY (46 journals)
    - DATA BASE MANAGEMENT (14 journals)
    - DATA MINING (32 journals)
    - E-BUSINESS (22 journals)
    - E-LEARNING (28 journals)
    - ELECTRONIC DATA PROCESSING (22 journals)
    - IMAGE AND VIDEO PROCESSING (39 journals)
    - INFORMATION SYSTEMS (109 journals)
    - INTERNET (94 journals)
    - SOCIAL WEB (51 journals)
    - SOFTWARE (34 journals)
    - THEORY OF COMPUTING (8 journals)

COMPUTER SCIENCE (1196 journals)                  1 2 3 4 5 6 | Last

Showing 1 - 200 of 872 Journals sorted alphabetically
3D Printing and Additive Manufacturing     Full-text available via subscription   (Followers: 20)
Abakós     Open Access   (Followers: 4)
ACM Computing Surveys     Hybrid Journal   (Followers: 22)
ACM Journal on Computing and Cultural Heritage     Hybrid Journal   (Followers: 8)
ACM Journal on Emerging Technologies in Computing Systems     Hybrid Journal   (Followers: 11)
ACM Transactions on Accessible Computing (TACCESS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Algorithms (TALG)     Hybrid Journal   (Followers: 15)
ACM Transactions on Applied Perception (TAP)     Hybrid Journal   (Followers: 5)
ACM Transactions on Architecture and Code Optimization (TACO)     Hybrid Journal   (Followers: 9)
ACM Transactions on Autonomous and Adaptive Systems (TAAS)     Hybrid Journal   (Followers: 7)
ACM Transactions on Computation Theory (TOCT)     Hybrid Journal   (Followers: 12)
ACM Transactions on Computational Logic (TOCL)     Hybrid Journal   (Followers: 3)
ACM Transactions on Computer Systems (TOCS)     Hybrid Journal   (Followers: 17)
ACM Transactions on Computer-Human Interaction     Hybrid Journal   (Followers: 14)
ACM Transactions on Computing Education (TOCE)     Hybrid Journal   (Followers: 5)
ACM Transactions on Design Automation of Electronic Systems (TODAES)     Hybrid Journal   (Followers: 3)
ACM Transactions on Economics and Computation     Hybrid Journal  
ACM Transactions on Embedded Computing Systems (TECS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Information Systems (TOIS)     Hybrid Journal   (Followers: 19)
ACM Transactions on Intelligent Systems and Technology (TIST)     Hybrid Journal   (Followers: 7)
ACM Transactions on Interactive Intelligent Systems (TiiS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)     Hybrid Journal   (Followers: 9)
ACM Transactions on Reconfigurable Technology and Systems (TRETS)     Hybrid Journal   (Followers: 6)
ACM Transactions on Sensor Networks (TOSN)     Hybrid Journal   (Followers: 7)
ACM Transactions on Speech and Language Processing (TSLP)     Hybrid Journal   (Followers: 8)
ACM Transactions on Storage     Hybrid Journal  
ACS Applied Materials & Interfaces     Full-text available via subscription   (Followers: 27)
Acta Automatica Sinica     Full-text available via subscription   (Followers: 2)
Acta Universitatis Cibiniensis. Technical Series     Open Access  
Ad Hoc Networks     Hybrid Journal   (Followers: 11)
Adaptive Behavior     Hybrid Journal   (Followers: 11)
Advanced Engineering Materials     Hybrid Journal   (Followers: 28)
Advanced Science Letters     Full-text available via subscription   (Followers: 9)
Advances in Adaptive Data Analysis     Hybrid Journal   (Followers: 7)
Advances in Artificial Intelligence     Open Access   (Followers: 15)
Advances in Calculus of Variations     Hybrid Journal   (Followers: 2)
Advances in Catalysis     Full-text available via subscription   (Followers: 5)
Advances in Computational Mathematics     Hybrid Journal   (Followers: 18)
Advances in Computer Science : an International Journal     Open Access   (Followers: 15)
Advances in Computing     Open Access   (Followers: 2)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 51)
Advances in Engineering Software     Hybrid Journal   (Followers: 27)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 13)
Advances in Human Factors/Ergonomics     Full-text available via subscription   (Followers: 23)
Advances in Human-Computer Interaction     Open Access   (Followers: 19)
Advances in Materials Sciences     Open Access   (Followers: 14)
Advances in Operations Research     Open Access   (Followers: 12)
Advances in Parallel Computing     Full-text available via subscription   (Followers: 6)
Advances in Porous Media     Full-text available via subscription   (Followers: 5)
Advances in Remote Sensing     Open Access   (Followers: 43)
Advances in Science and Research (ASR)     Open Access   (Followers: 4)
Advances in Technology Innovation     Open Access   (Followers: 5)
AEU - International Journal of Electronics and Communications     Hybrid Journal   (Followers: 8)
African Journal of Information and Communication     Open Access   (Followers: 6)
African Journal of Mathematics and Computer Science Research     Open Access   (Followers: 4)
AI EDAM     Hybrid Journal  
Air, Soil & Water Research     Open Access   (Followers: 11)
AIS Transactions on Human-Computer Interaction     Open Access   (Followers: 5)
Algebras and Representation Theory     Hybrid Journal   (Followers: 1)
Algorithms     Open Access   (Followers: 11)
American Journal of Computational and Applied Mathematics     Open Access   (Followers: 5)
American Journal of Computational Mathematics     Open Access   (Followers: 4)
American Journal of Information Systems     Open Access   (Followers: 5)
American Journal of Sensor Technology     Open Access   (Followers: 4)
Anais da Academia Brasileira de Ciências     Open Access   (Followers: 2)
Analog Integrated Circuits and Signal Processing     Hybrid Journal   (Followers: 7)
Analysis in Theory and Applications     Hybrid Journal   (Followers: 1)
Animation Practice, Process & Production     Hybrid Journal   (Followers: 5)
Annals of Combinatorics     Hybrid Journal   (Followers: 3)
Annals of Data Science     Hybrid Journal   (Followers: 11)
Annals of Mathematics and Artificial Intelligence     Hybrid Journal   (Followers: 12)
Annals of Pure and Applied Logic     Open Access   (Followers: 2)
Annals of Software Engineering     Hybrid Journal   (Followers: 13)
Annual Reviews in Control     Hybrid Journal   (Followers: 6)
Anuario Americanista Europeo     Open Access  
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 2)
Applied and Computational Harmonic Analysis     Full-text available via subscription   (Followers: 1)
Applied Artificial Intelligence: An International Journal     Hybrid Journal   (Followers: 13)
Applied Categorical Structures     Hybrid Journal   (Followers: 2)
Applied Clinical Informatics     Hybrid Journal   (Followers: 2)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 11)
Applied Computer Systems     Open Access   (Followers: 2)
Applied Informatics     Open Access  
Applied Mathematics and Computation     Hybrid Journal   (Followers: 33)
Applied Medical Informatics     Open Access   (Followers: 10)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 5)
Applied Soft Computing     Hybrid Journal   (Followers: 16)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 4)
Applied System Innovation     Open Access  
Architectural Theory Review     Hybrid Journal   (Followers: 3)
Archive of Applied Mechanics     Hybrid Journal   (Followers: 5)
Archive of Numerical Software     Open Access  
Archives and Museum Informatics     Hybrid Journal   (Followers: 130)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 5)
arq: Architectural Research Quarterly     Hybrid Journal   (Followers: 7)
Artifact     Hybrid Journal   (Followers: 2)
Artificial Life     Hybrid Journal   (Followers: 7)
Asia Pacific Journal on Computational Engineering     Open Access  
Asia-Pacific Journal of Information Technology and Multimedia     Open Access   (Followers: 1)
Asian Journal of Computer Science and Information Technology     Open Access  
Asian Journal of Control     Hybrid Journal  
Assembly Automation     Hybrid Journal   (Followers: 2)
at - Automatisierungstechnik     Hybrid Journal   (Followers: 1)
Australian Educational Computing     Open Access   (Followers: 1)
Automatic Control and Computer Sciences     Hybrid Journal   (Followers: 4)
Automatic Documentation and Mathematical Linguistics     Hybrid Journal   (Followers: 5)
Automatica     Hybrid Journal   (Followers: 11)
Automation in Construction     Hybrid Journal   (Followers: 6)
Autonomous Mental Development, IEEE Transactions on     Hybrid Journal   (Followers: 9)
Basin Research     Hybrid Journal   (Followers: 5)
Behaviour & Information Technology     Hybrid Journal   (Followers: 53)
Big Data and Cognitive Computing     Open Access   (Followers: 2)
Biodiversity Information Science and Standards     Open Access  
Bioinformatics     Hybrid Journal   (Followers: 281)
Biomedical Engineering     Hybrid Journal   (Followers: 15)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 13)
Biomedical Engineering, IEEE Reviews in     Full-text available via subscription   (Followers: 19)
Biomedical Engineering, IEEE Transactions on     Hybrid Journal   (Followers: 35)
Briefings in Bioinformatics     Hybrid Journal   (Followers: 43)
British Journal of Educational Technology     Hybrid Journal   (Followers: 142)
Broadcasting, IEEE Transactions on     Hybrid Journal   (Followers: 10)
c't Magazin fuer Computertechnik     Full-text available via subscription   (Followers: 1)
CALCOLO     Hybrid Journal  
Calphad     Hybrid Journal  
Canadian Journal of Electrical and Computer Engineering     Full-text available via subscription   (Followers: 14)
Capturing Intelligence     Full-text available via subscription  
Catalysis in Industry     Hybrid Journal   (Followers: 1)
CEAS Space Journal     Hybrid Journal   (Followers: 2)
Cell Communication and Signaling     Open Access   (Followers: 2)
Central European Journal of Computer Science     Hybrid Journal   (Followers: 5)
CERN IdeaSquare Journal of Experimental Innovation     Open Access   (Followers: 2)
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 3)
Chemometrics and Intelligent Laboratory Systems     Hybrid Journal   (Followers: 14)
ChemSusChem     Hybrid Journal   (Followers: 7)
China Communications     Full-text available via subscription   (Followers: 7)
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 2)
CIN Computers Informatics Nursing     Full-text available via subscription   (Followers: 11)
Circuits and Systems     Open Access   (Followers: 15)
Clean Air Journal     Full-text available via subscription   (Followers: 1)
CLEI Electronic Journal     Open Access  
Clin-Alert     Hybrid Journal   (Followers: 1)
Cluster Computing     Hybrid Journal   (Followers: 1)
Cognitive Computation     Hybrid Journal   (Followers: 4)
COMBINATORICA     Hybrid Journal  
Combinatorics, Probability and Computing     Hybrid Journal   (Followers: 4)
Combustion Theory and Modelling     Hybrid Journal   (Followers: 14)
Communication Methods and Measures     Hybrid Journal   (Followers: 12)
Communication Theory     Hybrid Journal   (Followers: 20)
Communications Engineer     Hybrid Journal   (Followers: 1)
Communications in Algebra     Hybrid Journal   (Followers: 3)
Communications in Computational Physics     Full-text available via subscription   (Followers: 2)
Communications in Partial Differential Equations     Hybrid Journal   (Followers: 3)
Communications of the ACM     Full-text available via subscription   (Followers: 52)
Communications of the Association for Information Systems     Open Access   (Followers: 16)
COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering     Hybrid Journal   (Followers: 3)
Complex & Intelligent Systems     Open Access   (Followers: 1)
Complex Adaptive Systems Modeling     Open Access  
Complex Analysis and Operator Theory     Hybrid Journal   (Followers: 2)
Complexity     Hybrid Journal   (Followers: 6)
Complexus     Full-text available via subscription  
Composite Materials Series     Full-text available via subscription   (Followers: 8)
Computación y Sistemas     Open Access  
Computation     Open Access  
Computational and Applied Mathematics     Hybrid Journal   (Followers: 2)
Computational and Mathematical Methods in Medicine     Open Access   (Followers: 2)
Computational and Mathematical Organization Theory     Hybrid Journal   (Followers: 2)
Computational and Structural Biotechnology Journal     Open Access   (Followers: 2)
Computational and Theoretical Chemistry     Hybrid Journal   (Followers: 9)
Computational Astrophysics and Cosmology     Open Access   (Followers: 1)
Computational Biology and Chemistry     Hybrid Journal   (Followers: 11)
Computational Chemistry     Open Access   (Followers: 2)
Computational Cognitive Science     Open Access   (Followers: 2)
Computational Complexity     Hybrid Journal   (Followers: 4)
Computational Condensed Matter     Open Access  
Computational Ecology and Software     Open Access   (Followers: 9)
Computational Economics     Hybrid Journal   (Followers: 9)
Computational Geosciences     Hybrid Journal   (Followers: 15)
Computational Linguistics     Open Access   (Followers: 23)
Computational Management Science     Hybrid Journal  
Computational Mathematics and Modeling     Hybrid Journal   (Followers: 8)
Computational Mechanics     Hybrid Journal   (Followers: 5)
Computational Methods and Function Theory     Hybrid Journal  
Computational Molecular Bioscience     Open Access   (Followers: 2)
Computational Optimization and Applications     Hybrid Journal   (Followers: 7)
Computational Particle Mechanics     Hybrid Journal   (Followers: 1)
Computational Research     Open Access   (Followers: 1)
Computational Science and Discovery     Full-text available via subscription   (Followers: 2)
Computational Science and Techniques     Open Access  
Computational Statistics     Hybrid Journal   (Followers: 14)
Computational Statistics & Data Analysis     Hybrid Journal   (Followers: 30)
Computer     Full-text available via subscription   (Followers: 94)
Computer Aided Surgery     Hybrid Journal   (Followers: 6)
Computer Applications in Engineering Education     Hybrid Journal   (Followers: 8)
Computer Communications     Hybrid Journal   (Followers: 10)
Computer Engineering and Applications Journal     Open Access   (Followers: 5)
Computer Journal     Hybrid Journal   (Followers: 9)
Computer Methods in Applied Mechanics and Engineering     Hybrid Journal   (Followers: 23)
Computer Methods in Biomechanics and Biomedical Engineering     Hybrid Journal   (Followers: 12)
Computer Methods in the Geosciences     Full-text available via subscription   (Followers: 2)
Computer Music Journal     Hybrid Journal   (Followers: 19)

        1 2 3 4 5 6 | Last

Journal Cover Advances in Data Analysis and Classification
  [SJR: 1.113]   [H-I: 14]   [51 followers]  Follow
    
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 1862-5355 - ISSN (Online) 1862-5347
   Published by Springer-Verlag Homepage  [2352 journals]
  • Editorial for Special Issue on Analysis of Asymmetric Relationships
    • Authors: Giuseppe Bove; Akinori Okada
      Pages: 1 - 4
      PubDate: 2018-03-01
      DOI: 10.1007/s11634-018-0315-4
      Issue No: Vol. 12, No. 1 (2018)
       
  • Skew symmetry in retrospect
    • Authors: John C. Gower
      Pages: 33 - 41
      Abstract: The paper gives a short account of how I became interested in analysing asymmetry in square tables. The early history of the canonical analysis of skew-symmetry and the associated development of its geometrical interpretation are described.
      PubDate: 2018-03-01
      DOI: 10.1007/s11634-014-0181-7
      Issue No: Vol. 12, No. 1 (2018)
       
  • CLUSKEXT: CLUstering model for SKew-symmetric data including EXTernal
           information
    • Authors: Donatella Vicari
      Pages: 43 - 64
      Abstract: A CLUstering model for SKew-symmetric data including EXTernal information (CLUSKEXT) is proposed, which relies on the decomposition of a skew-symmetric matrix into within and between cluster effects which are further decomposed into regression and residual effects when possible external information on the objects is available. In order to fit the imbalances between objects, the model jointly searches for a partition of objects and appropriate weights which are in turn linearly linked to the external variables. The proposal is fitted in a least-squares framework and a decomposition of the fit is derived. An appropriate Alternating Least-Squares algorithm is provided to fit the model to illustrative real and artificial data.
      PubDate: 2018-03-01
      DOI: 10.1007/s11634-015-0203-0
      Issue No: Vol. 12, No. 1 (2018)
       
  • Hierarchical clustering of asymmetric networks
    • Authors: Gunnar Carlsson; Facundo Mémoli; Alejandro Ribeiro; Santiago Segarra
      Pages: 65 - 105
      Abstract: This paper considers networks where relationships between nodes are represented by directed dissimilarities. The goal is to study methods that, based on the dissimilarity structure, output hierarchical clusters, i.e., a family of nested partitions indexed by a connectivity parameter. Our construction of hierarchical clustering methods is built around the concept of admissible methods, which are those that abide by the axioms of value—nodes in a network with two nodes are clustered together at the maximum of the two dissimilarities between them—and transformation—when dissimilarities are reduced, the network may become more clustered but not less. Two particular methods, termed reciprocal and nonreciprocal clustering, are shown to provide upper and lower bounds in the space of admissible methods. Furthermore, alternative clustering methodologies and axioms are considered. In particular, modifying the axiom of value such that clustering in two-node networks occurs at the minimum of the two dissimilarities entails the existence of a unique admissible clustering method. Finally, the developed clustering methods are implemented to analyze the internal migration in the United States.
      PubDate: 2018-03-01
      DOI: 10.1007/s11634-017-0299-5
      Issue No: Vol. 12, No. 1 (2018)
       
  • Transitional modeling of experimental longitudinal data with missing
           values
    • Authors: Mark de Rooij
      Pages: 107 - 130
      Abstract: Longitudinal categorical data are often collected using an experimental design where the interest is in the differential development of the treatment group compared to the control group. Such differential development is often assessed based on average growth curves but can also be based on transitions. For longitudinal multinomial data we describe a transitional methodology for the statistical analysis based on a distance model. Such a distance approach has two advantages compared to a multinomial regression model: (1) sparse data can be handled more efficiently; (2) a graphical representation of the model can be made to enhance interpretation. Within this approach it is possible to jointly model the observations and missing values by adding a new category to the response variable representing the missingness condition. This approach is investigated in a Monte Carlo simulation study. The results show this is a promising way to deal with missing data, although the mechanism is not yet completely understood in all cases. Finally, an empirical example is presented where the advantages of the modeling procedure are highlighted.
      PubDate: 2018-03-01
      DOI: 10.1007/s11634-015-0226-6
      Issue No: Vol. 12, No. 1 (2018)
       
  • Assessing the asymmetric effects on branch rivalry of Spanish financial
           sector restructuring
    • Authors: Marti Sagarra; Frank M. T. A. Busing; Cecilio Mar-Molinero; Josep Rialp
      Pages: 131 - 153
      Abstract: Spanish financial institutions have been heavily affected by the banking crisis that began in 2008. Many of them, especially Spanish savings banks (or Cajas), had to merge with other institutions or had to be rescued. We address the question of up to what point the nature of competition in this sector has changed as a result of the crisis. Although institutions compete in many ways, we concentrate on their presence in the main street through bank branches open to the public (i.e., retail banking competition). Our measure of inter-firm rivalry is based on a geographical proximity measure that we calculate for the years 2008 (before the crisis) and 2012 (the last available data set). The technical approach is based on multidimensional unfolding, a methodology which allows us to graphically represent the asymmetric nature of such rivalry. These maps visualise the salient aspects of the system during the two dates analysed, and can be understood without a detailed technical knowledge.
      PubDate: 2018-03-01
      DOI: 10.1007/s11634-014-0186-2
      Issue No: Vol. 12, No. 1 (2018)
       
  • Relating brand confusion to ad similarities and brand strengths through
           image data analysis and classification
    • Authors: Daniel Baier; Sarah Frost
      Pages: 155 - 171
      Abstract: Brand confusion occurs when a consumer is exposed to an advertisement (ad) for brand A but believes that it is for brand B. If more consumers are confused in this direction than in the other one (assuming that an ad for B is for A), this asymmetry is a disadvantage for A. Consequently, the confusion potential and structure of ads has to be checked: A sample of consumers is exposed to a sample of ads. For each ad the consumers have to specify their guess about the advertised brand. Then, the collected data are aggregated and analyzed using, e.g., MDS or two-mode clustering. In this paper we compare this approach to a new one where image data analysis and classification is applied: The confusion potential and structure of ads is related to featurewise distances between ads and—to model asymmetric effects—to the strengths of the advertised brands. A sample application for the German beer market is presented, the results are encouraging.
      PubDate: 2018-03-01
      DOI: 10.1007/s11634-017-0282-1
      Issue No: Vol. 12, No. 1 (2018)
       
  • Linear components of quadratic classifiers
    • Authors: José R. Berrendero; Javier Cárcamo
      Abstract: We obtain a decomposition of any quadratic classifier in terms of products of hyperplanes. These hyperplanes can be viewed as relevant linear components of the quadratic rule (with respect to the underlying classification problem). As an application, we introduce the associated multidirectional classifier; a piecewise linear classification rule induced by the approximating products. Such a classifier is useful to determine linear combinations of the predictor variables with ability to discriminate. We also show that this classifier can be used as a tool to reduce the dimension of the data and helps identify the most important variables to classify new elements. Finally, we illustrate with a real data set the use of these linear components to construct oblique classification trees.
      PubDate: 2018-04-07
      DOI: 10.1007/s11634-018-0321-6
       
  • A bivariate index vector for measuring departure from double symmetry in
           square contingency tables
    • Authors: Shuji Ando; Kouji Tahata; Sadao Tomizawa
      Abstract: For square contingency tables, a double symmetry model having a matrix structure that combines both symmetry and point symmetry was proposed. Also, an index which represents the degree of departure from double symmetry was proposed. However, this index cannot simultaneously characterize the degree of departure from symmetry and the degree of departure from point symmetry. For measuring the degree of departure from double symmetry, the present paper proposes a bivariate index vector that can simultaneously characterize the degree of departure from symmetry and the degree of departure from point symmetry.
      PubDate: 2018-03-26
      DOI: 10.1007/s11634-018-0320-7
       
  • An efficient random forests algorithm for high dimensional data
           classification
    • Authors: Qiang Wang; Thanh-Tung Nguyen; Joshua Z. Huang; Thuy Thi Nguyen
      Abstract: In this paper, we propose a new random forest (RF) algorithm to deal with high dimensional data for classification using subspace feature sampling method and feature value searching. The new subspace sampling method maintains the diversity and randomness of the forest and enables one to generate trees with a lower prediction error. A greedy technique is used to handle cardinal categorical features for efficient node splitting when building decision trees in the forest. This allows trees to handle very high cardinality meanwhile reducing computational time in building the RF model. Extensive experiments on high dimensional real data sets including standard machine learning data sets and image data sets have been conducted. The results demonstrated that the proposed approach for learning RFs significantly reduced prediction errors and outperformed most existing RFs when dealing with high-dimensional data.
      PubDate: 2018-03-21
      DOI: 10.1007/s11634-018-0318-1
       
  • Properties of Bangdiwala’s B
    • Authors: Matthijs J. Warrens; Alexandra de Raadt
      Abstract: Cohen’s kappa is the most widely used coefficient for assessing interobserver agreement on a nominal scale. An alternative coefficient for quantifying agreement between two observers is Bangdiwala’s B. To provide a proper interpretation of an agreement coefficient one must first understand its meaning. Properties of the kappa coefficient have been extensively studied and are well documented. Properties of coefficient B have been studied, but not extensively. In this paper, various new properties of B are presented. Category B-coefficients are defined that are the basic building blocks of B. It is studied how coefficient B, Cohen’s kappa, the observed agreement and associated category coefficients may be related. It turns out that the relationships between the coefficients are quite different for \(2\times 2\) tables than for agreement tables with three or more categories.
      PubDate: 2018-03-19
      DOI: 10.1007/s11634-018-0319-0
       
  • Mixtures of restricted skew- t factor analyzers with common factor
           loadings
    • Authors: Wan-Lun Wang; Luis M. Castro; Yen-Ting Chang; Tsung-I Lin
      Abstract: Mixtures of common t factor analyzers (MCtFA) have been shown its effectiveness in robustifying mixtures of common factor analyzers (MCFA) when handling model-based clustering of the high-dimensional data with heavy tails. However, the MCtFA model may still suffer from a lack of robustness against observations whose distributions are highly asymmetric. This paper presents a further robust extension of the MCFA and MCtFA models, called the mixture of common restricted skew-t factor analyzers (MCrstFA), by assuming a restricted multivariate skew-t distribution for the common factors. The MCrstFA model can be used to accommodate severely non-normal (skewed and leptokurtic) random phenomena while preserving its parsimony in factor-analytic representation and performing graphical visualization in low-dimensional plots. A computationally feasible expectation conditional maximization either algorithm is developed to carry out maximum likelihood estimation. The numbers of factors and mixture components are simultaneously determined based on common likelihood penalized criteria. The usefulness of our proposed model is illustrated with simulated and real datasets, and experimental results signify its superiority over some existing competitors.
      PubDate: 2018-03-08
      DOI: 10.1007/s11634-018-0317-2
       
  • Equi-Clustream: a framework for clustering time evolving mixed data
    • Authors: Ravi Sankar Sangam; Hari Om
      Abstract: In data stream environment, most of the conventional clustering algorithms are not sufficiently efficient, since large volumes of data arrive in a stream and these data points unfold with time. The problem of clustering time-evolving metric data and categorical time-evolving data has separately been well explored in recent years, but the problem of clustering mixed type time-evolving data remains a challenging issue due to an awkward gap between the structure of metric and categorical attributes. In this paper, we devise a generalized framework, termed Equi-Clustream to dynamically cluster mixed type time-evolving data, which comprises three algorithms: a Hybrid Drifting Concept Detection Algorithm that detects the drifting concept between the current sliding window and previous sliding window, a Hybrid Data Labeling Algorithm that assigns an appropriate cluster label to each data vector of the current non-drifting window based on the clustering result of the previous sliding window, and a visualization algorithm that analyses the relationship between the clusters at different timestamps and also visualizes the evolving trends of the clusters. The efficacy of the proposed framework is shown by experiments on synthetic and real world datasets.
      PubDate: 2018-02-26
      DOI: 10.1007/s11634-018-0316-3
       
  • Model-based approach for household clustering with mixed scale variables
    • Authors: Christian Carmona; Luis Nieto-Barajas; Antonio Canale
      Abstract: The Ministry of Social Development in Mexico is in charge of creating and assigning social programmes targeting specific needs in the population for the improvement of the quality of life. To better target the social programmes, the Ministry is aimed to find clusters of households with the same needs based on demographic characteristics as well as poverty conditions of the household. Available data consists of continuous, ordinal, and nominal variables, all of which come from a non-i.i.d complex design survey sample. We propose a Bayesian nonparametric mixture model that jointly models a set of latent variables, as in an underlying variable response approach, associated to the observed mixed scale data and accommodates for the different sampling probabilities. The performance of the model is assessed via simulated data. A full analysis of socio-economic conditions in households in the Mexican State of Mexico is presented.
      PubDate: 2018-02-08
      DOI: 10.1007/s11634-018-0313-6
       
  • Clustering space-time series: FSTAR as a flexible STAR approach
    • Authors: Edoardo Otranto; Massimo Mucciardi
      Abstract: The STAR model is widely used to represent the dynamics of a certain variable recorded at several locations at the same time. Its advantages are often discussed in terms of parsimony with respect to space-time VAR structures because it considers a single coefficient for each time and spatial lag. This hypothesis can be very strong; we add a certain degree of flexibility to the STAR model, providing the possibility for coefficients to vary in groups of locations. The new class of models (called Flexible STAR–FSTAR) is compared to the classical STAR and the space-time VAR by simulations and an application.
      PubDate: 2018-02-07
      DOI: 10.1007/s11634-018-0314-5
       
  • Robust clustering for functional data based on trimming and constraints
    • Abstract: Many clustering algorithms when the data are curves or functions have been recently proposed. However, the presence of contamination in the sample of curves can influence the performance of most of them. In this work we propose a robust, model-based clustering method that relies on an approximation to the “density function” for functional data. The robustness follows from the joint application of data-driven trimming, for reducing the effect of contaminated observations, and constraints on the variances, for avoiding spurious clusters in the solution. The algorithm is designed to perform clustering and outlier detection simultaneously by maximizing a trimmed “pseudo” likelihood. The proposed method has been evaluated and compared with other existing methods through a simulation study. Better performance for the proposed methodology is shown when a fraction of contaminating curves is added to a non-contaminated sample. Finally, an application to a real data set that has been previously considered in the literature is given.
      PubDate: 2018-02-03
      DOI: 10.1007/s11634-018-0312-7
       
  • Methods for the analysis of asymmetric pairwise relationships
    • Authors: Giuseppe Bove; Akinori Okada
      Abstract: Asymmetric pairwise relationships are frequently observed in experimental and non-experimental studies. They can be analysed with different aims and approaches. A brief review of models and methods of multidimensional scaling and cluster analysis able to deal with asymmetric proximities is provided taking a ‘data-analytic’ approach and emphasizing data visualization.
      PubDate: 2018-02-01
      DOI: 10.1007/s11634-017-0307-9
       
  • A method for selecting the relevant dimensions for high-dimensional
           classification in singular vector spaces
    • Authors: Dawit G. Tadesse; Mark Carpenter
      Abstract: In this paper, we give a new feature selection algorithm for the binary class classification problem in sparse high-dimensional spaces. Singular value decomposition (SVD) is a popular dimension reduction method in higher-dimensional classification. The traditional SVD method begins by ranking the Singular Dimensions (SDs) from largest singular value to the smallest. However, when the number of signals is fewer than the number of noise, the first few ranked SDs are not necessarily the best for classification. We demonstrate, theoretically and empirically, that our method efficiently selects the SDs most appropriate for classification and significantly reduces the misclassification error. We also apply our method to real data text mining applications.
      PubDate: 2018-01-25
      DOI: 10.1007/s11634-018-0311-8
       
  • Comparisons among several methods for handling missing data in principal
           component analysis (PCA)
    • Authors: Sébastien Loisel; Yoshio Takane
      Abstract: Missing data are prevalent in many data analytic situations. Those in which principal component analysis (PCA) is applied are no exceptions. The performance of five methods for handling missing data in PCA is investigated, the missing data passive method, the weighted low rank approximation (WLRA) method, the regularized PCA (RPCA) method, the trimmed scores regression method, and the data augmentation (DA) method. Three complete data sets of varying sizes were selected, in which missing data were created randomly and non-randomly. These data were then analyzed by the five methods, and their parameter recovery capability, as measured by the mean congruence coefficient between loadings obtained from full and missing data, is compared as functions of the number of extracted components (dimensionality) and the proportion of missing data (censor rate). For randomly censored data, all five methods worked well when the dimensionality and censor rate were small. Their performance deteriorated, as the dimensionality and censor rate increased, but the speed of deterioration was distinctly faster with the WLRA method. The RPCA method worked best and the DA method came as a close second in terms of parameter recovery. However, the latter, as implemented here, was found to be extremely time-consuming. For non-randomly censored data, the recovery was also affected by the degree of non-randomness in censoring processes. Again the RPCA method worked best, maintaining good to excellent recoveries when the censor rate was small and the dimensionality of solutions was not too excessive.
      PubDate: 2018-01-18
      DOI: 10.1007/s11634-018-0310-9
       
  • New distance measures for classifying X-ray astronomy data into stellar
           classes
    • Authors: Amparo Baíllo; Javier Cárcamo; Konstantin Getman
      Abstract: The classification of the X-ray sources into classes (such as extragalactic sources, background stars,...) is an essential task in astronomy. Typically, one of the classes corresponds to extragalactic radiation, whose photon emission behaviour is well characterized by a homogeneous Poisson process. We propose to use normalized versions of the Wasserstein and Zolotarev distances to quantify the deviation of the distribution of photon interarrival times from the exponential class. Our main motivation is the analysis of a massive dataset from X-ray astronomy obtained by the Chandra Orion Ultradeep Project (COUP). This project yielded a large catalog of 1616 X-ray cosmic sources in the Orion Nebula region, with their series of photon arrival times and associated energies. We consider the plug-in estimators of these metrics, determine their asymptotic distributions, and illustrate their finite-sample performance with a Monte Carlo study. We estimate these metrics for each COUP source from three different classes. We conclude that our proposal provides a striking amount of information on the nature of the photon emitting sources. Further, these variables have the ability to identify X-ray sources wrongly catalogued before. As an appealing conclusion, we show that some sources, previously classified as extragalactic emissions, have a much higher probability of being young stars in Orion Nebula.
      PubDate: 2018-01-18
      DOI: 10.1007/s11634-018-0309-2
       
 
 
JournalTOCs
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Email: journaltocs@hw.ac.uk
Tel: +00 44 (0)131 4513762
Fax: +00 44 (0)131 4513327
 
Home (Search)
Subjects A-Z
Publishers A-Z
Customise
APIs
Your IP address: 54.81.71.187
 
About JournalTOCs
API
Help
News (blog, publications)
JournalTOCs on Twitter   JournalTOCs on Facebook

JournalTOCs © 2009-