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Interpreting large visual similarity matrices

C. Mueller, B. Martin, A. Lumsdaine
2007 2007 6th International Asia-Pacific Symposium on Visualization  
Visual similarity matrices (VSMs) are a common technique for visualizing graphs and other types of relational data.  ...  While traditionally used for small data sets or well-ordered large data sets, they have recently become popular for visualizing large graphs.  ...  CONCLUSION Visual similarity matrices are a powerful tool for exploring very large data sets.  ... 
doi:10.1109/apvis.2007.329290 dblp:conf/apvis/MuellerML07a fatcat:ntnrq7wdpfajbh6n54wfvvjlyi

A comparison of vertex ordering algorithms for large graph visualization

C. Mueller, B. Martin, A. Lumsdaine
2007 2007 6th International Asia-Pacific Symposium on Visualization  
In this study, we examine the use of graph ordering algorithms for visual analysis of data sets using visual similarity matrices.  ...  Visual similarity matrices display the relationships between data items in a dot-matrix plot format, with the axes labeled with the data items and points drawn if there is a relationship between two data  ...  Thus, visual similarity matrices are an attractive solution for large graph visualization.  ... 
doi:10.1109/apvis.2007.329289 dblp:conf/apvis/MuellerML07 fatcat:vmv4fgekmzajriawtw5xp3m7dy

Visual Analysis of Sets of Heterogeneous Matrices Using Projection-Based Distance Functions and Semantic Zoom

Michael Behrisch, James Davey, Fabian Fischer, Olivier Thonnard, Tobias Schreck, Daniel Keim, Jörn Kohlhammer
2014 Computer graphics forum (Print)  
A key advantage of this measure is that it can be interpreted and manipulated as a visual distance function, and serves as a comprehensible basis for ranking, clustering and comparison in sets of matrices  ...  Matrix visualization is an established technique in the analysis of relational data. It is applicable to large, dense networks, where node-link representations may not be effective.  ...  In [EDG * 08, AvH04] zooming and dynamic aggregation techniques support the navigation process in large matrices. Matrices, and thus matrix visualizations, occur in many real-world analysis tasks.  ... 
doi:10.1111/cgf.12397 fatcat:ns3xgsy35rdcvmrpcl37tiwa5a

The Effects of Representation and Juxtaposition on Graphical Perception of Matrix Visualization

Xiaotong Liu, Han-Wei Shen
2015 Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems - CHI '15  
With the design guidelines derived from our studies, we present a compact visualization termed TileMatrix for juxtaposing a large number of matrices, and demonstrate its effectiveness in analyzing multi-faceted  ...  We evaluate various representations and juxtaposition designs for visualizing adjacency matrices through a series of controlled experiments.  ...  and complementary juxtaposition to display a large number of adjacency matrices.  ... 
doi:10.1145/2702123.2702217 dblp:conf/chi/LiuS15 fatcat:cetfmehutbcznk7v7witsc7p6a

Magnostics: Image-Based Search of Interesting Matrix Views for Guided Network Exploration

Michael Behrisch, Benjamin Bach, Michael Hund, Michael Delz, Laura Von Ruden, Jean-Daniel Fekete, Tobias Schreck
2017 IEEE Transactions on Visualization and Computer Graphics  
MAGNOSTICS can be used to analyze, query, or search for visually similar matrices in large collections, or to assess the quality of matrix reordering algorithms.  ...  We conclude with an informed set of six descriptors as most appropriate for MAGNOSTICS and demonstrate their application in two scenarios; exploring a large collection of matrices and analyzing temporal  ...  The authors thank the German Research Foundation (DFG) for financial support within project A03 "Quantification of Visual Analytics Transformations and Mappings" of SFB/Transregio 161.  ... 
doi:10.1109/tvcg.2016.2598467 pmid:27514053 fatcat:yq3tka373fba7eyvxhsttj7oee

A non-negative matrix factorization framework for identifying modular patterns in metagenomic profile data

Xingpeng Jiang, Joshua S. Weitz, Jonathan Dushoff
2011 Journal of Mathematical Biology  
In particular, we introduce a method for choosing NMF degree in the presence of overlap, and apply spectral-reordering techniques to NMF-based similarity matrices to aid visualization.  ...  It is thus well suited to interpretation of observed samples as combinations of different components. We develop, test and apply an NMF-based framework to analyze metagenomic read matrices.  ...  Acknowledgments The authors thank Simon Levin for inspiration and guidance over the years, and specifically for inspiring us to investigate the ecological interpretation of metagenomic data.  ... 
doi:10.1007/s00285-011-0428-2 pmid:21630089 fatcat:m5n5mt6azfbqtlzbh3of2jeqbq

Visualizing dimensionality reduction of systems biology data

Andreas Lehrmann, Michael Huber, Aydin C. Polatkan, Albert Pritzkau, Kay Nieselt
2012 Data mining and knowledge discovery  
Different visualizations of these measures can be combined with functional annotations that support the interpretation of the results.  ...  This includes measures that assist the interpretation of the factorization result.  ...  Pritzkau were supported by the DFG Priority Program 1335 "Scalable Visual Analytics".  ... 
doi:10.1007/s10618-012-0268-8 fatcat:hf4ghnoskfearbhe46j7z4vgrq

Examining Similarity Structure: Multidimensional Scaling and Related Approaches in Neuroimaging

Svetlana V. Shinkareva, Jing Wang, Douglas H. Wedell
2013 Computational and Mathematical Methods in Medicine  
We highlight unique contributions of these methods by reviewing recent applications to functional magnetic resonance imaging data and emphasize areas of caution in applying and interpreting similarity  ...  This paper covers similarity analyses, a subset of multivariate pattern analysis techniques that are based on similarity spaces defined by multivariate patterns.  ...  On the other extreme, if the differences between individual proximity matrices are not systematic, interpreting the differences is not meaningful.  ... 
doi:10.1155/2013/796183 pmid:23662162 pmcid:PMC3639644 fatcat:b5vyoqk36fe7piommuku4sul4e

HiPiler: Visual Exploration of Large Genome Interaction Matrices with Interactive Small Multiples

Fritz Lekschas, Benjamin Bach, Peter Kerpedjiev, Nils Gehlenborg, Hanspeter Pfister
2018 IEEE Transactions on Visualization and Computer Graphics  
Abstract-This paper presents an interactive visualization interface-HiPiler-for the exploration and visualization of regions-of-interest in large genome interaction matrices.  ...  The design of HiPiler is based on a series of semi-structured interviews with 10 domain experts involved in the analysis and interpretation of genome interaction matrices.  ...  Visualizing Large Matrices Matrices are a common representation for visualizing networks or graphs [6, 43] . Thus, we briefly overview related visualization techniques that focus on large matrices.  ... 
doi:10.1109/tvcg.2017.2745978 pmid:28866592 pmcid:PMC6038708 fatcat:44asv6jbjze6zdoytkpqv76dkq

HiPiler: Visual Exploration Of Large Genome Interaction Matrices With Interactive Small Multiples [article]

Fritz Lekschas, Benjamin Bach, Peter Kerpedjiev, Nils Gehlenborg, Hanspeter Pfister
2017 bioRxiv   pre-print
This paper presents an interactive visualization interface - HiPiler - for the exploration and visualization of regions-of-interest in large genome interaction matrices.  ...  The design of HiPiler is based on a series of semi-structured interviews with 10 domain experts involved in the analysis and interpretation of genome interaction matrices.  ...  Visualizing Large Matrices Matrices are a common representation for visualizing networks or graphs [6, 43] . Thus, we briefly overview related visualization techniques that focus on large matrices.  ... 
doi:10.1101/123588 fatcat:l6s4dvcztnhwnokbzu35yn2ebi

Corrgrams

Michael Friendly
2002 American Statistician  
matrices directly, particularly when the number of variables is moderately large.  ...  In addition, the extension of this visualization to matrices for conditional independence and partial independence is described and illustrated, and we provide an easily-used SAS implementation of these  ...  Ordering For example, Paolini and Santangelo (1991) use similar displays for visual analysis of the pattern of sparsity in the p p coefficient matrix, A, in large linear systems of the form Ax = b, where  ... 
doi:10.1198/000313002533 fatcat:uflzhxcgkrabtizioxixqrjtl4

Polarimetric sar image visualization and interpretation with covariance matrix invariants

Jaan Praks, Martti Hallikainen, Elise Colin Koeniguer
2010 2010 IEEE International Geoscience and Remote Sensing Symposium  
Large polarimetric SAR images require visualization schemes for image browsing and interpretation. Methods should be easy to understand and simple to implement.  ...  The presented polarimetric parametes are suitable for large images and have straightforward interpretation.  ... 
doi:10.1109/igarss.2010.5649395 dblp:conf/igarss/PraksHK10 fatcat:d2sccjghpnhwtaajlc7en4x34i

Characterizing Variability of Modular Brain Connectivity with Constrained Principal Component Analysis

Jun-ichiro Hirayama, Aapo Hyvärinen, Vesa Kiviniemi, Motoaki Kawanabe, Okito Yamashita, Satoru Hayasaka
2016 PLoS ONE  
The parametric constraint provides a compact modulebased visualization scheme with which the result can be intuitively interpreted.  ...  However, performing PCA on high-dimensional connectivity matrices yields complicated "eigenconnectivity" patterns, for which systematic interpretation is a challenging issue.  ...  symmetric matrices B 1 and B 2 define a two-dimensional subspace in the matrix space, along which observed matrices X n largely varied.  ... 
doi:10.1371/journal.pone.0168180 pmid:28002474 pmcid:PMC5176286 fatcat:5z2ijvcip5eshg4jmg4s6kjwnm

Page 1261 of Psychological Abstracts Vol. 61, Issue 6 [page]

1979 Psychological Abstracts  
These similarity matrices were tested against experimentally produced confusion matrices reported in the literature.  ...  The similarity matrices predict- ed Ss’ confusions poorly: The best predictions were made, not by any of the spatial frequency similarities, but by similarities between the original letter stimuli input  ... 

Interactive web application for exploring matrices of neural connectivity

David J. Caldwell, Jing Wu, Kaitlyn Casimo, Jeffrey G. Ojemann, Rajesh P.N. Rao
2017 2017 8th International IEEE/EMBS Conference on Neural Engineering (NER)  
We present here a browser-based application for visualizing patterns of connectivity in 3D stacked data matrices with large numbers of pairwise relations.  ...  of these connectivity matrices to highlight connections of interest.  ...  Interpreting neural connectivity is a challenging problem because cortical connectivity visualizations are largely exploratory and require the encoding of many multivariate attributes that exist for each  ... 
doi:10.1109/ner.2017.8008287 dblp:conf/ner/CaldwellWCOR17 fatcat:5lxss2rxzbax7pz5sqp5ylmd3u
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