24,397 research outputs found
Large Graph Analysis in the GMine System
Current applications have produced graphs on the order of hundreds of
thousands of nodes and millions of edges. To take advantage of such graphs, one
must be able to find patterns, outliers and communities. These tasks are better
performed in an interactive environment, where human expertise can guide the
process. For large graphs, though, there are some challenges: the excessive
processing requirements are prohibitive, and drawing hundred-thousand nodes
results in cluttered images hard to comprehend. To cope with these problems, we
propose an innovative framework suited for any kind of tree-like graph visual
design. GMine integrates (a) a representation for graphs organized as
hierarchies of partitions - the concepts of SuperGraph and Graph-Tree; and (b)
a graph summarization methodology - CEPS. Our graph representation deals with
the problem of tracing the connection aspects of a graph hierarchy with sub
linear complexity, allowing one to grasp the neighborhood of a single node or
of a group of nodes in a single click. As a proof of concept, the visual
environment of GMine is instantiated as a system in which large graphs can be
investigated globally and locally
Online visualization of bibliography Using Visualization Techniques
Visualization is a concept where we can represent some raw data in the form of graphs, images, charts, etc. which will be very helpful for the end-user to correlate and be able to understand the relationships between the data elements in a single screen. Representing the bibliographic information of the computer science journals and proceedings using Visualization technique would help user choose a particular author and navigate through the hierarchy and find out what papers the author has published, the keywords of the papers, what papers cite them, the co-authors along with the main author, and how many papers are published by the author selected by the user and so on in a single page. These information is right now present in a scattered manner and the user has to search on websites like Google Scholar [1], Cite Seer [2] to get these bibliographic records. By the use of visualization techniques, all the information can be accessed on a single page by having a graph like points on the page, where the user can search for a particular author and the author and its co-authors are represented in the form of points. The goal of this project is to enhance current bibliography web services with an intuitive interactive visualization interface and to improve user understanding and conceptualization. In this project, we develop a simple web-interface which will take a search query from the user and find the related information like author\u27s name, the co-authors, number of papers published by him, related keywords, citations referred etc. The project uses the bibliographic records which are available as XML files from the Citeseer database[2], extracts the data into the database and then queries the database for the results using a web service. The data which is extracted is then presented visually to allow the user to conceptualize the results in a better way and help him/her find the articles of interest with utmost ease. In addition the user can interactively navigate the visual results to get more information about any of the article or the author displayed. So here we present both paper centric view and author centric view to the user by representing data in terms of graphs. The nodes in the graphs obtained for paper centric views and author centric views are color coded based on the paper’s weight parameter ( popularity of the paper ). For the paper centric view, the papers which are referring other papers are represented by providing a directed arrow from referred paper to referenced paper. Overall the idea here was to represent this related data in the form of a tree, so that the user can correlate all the data and get the relationships between them
A parent-centered radial layout algorithm for interactive graph visualization and animation
We have developed (1) a graph visualization system that allows users to
explore graphs by viewing them as a succession of spanning trees selected
interactively, (2) a radial graph layout algorithm, and (3) an animation
algorithm that generates meaningful visualizations and smooth transitions
between graphs while minimizing edge crossings during transitions and in static
layouts.
Our system is similar to the radial layout system of Yee et al. (2001), but
differs primarily in that each node is positioned on a coordinate system
centered on its own parent rather than on a single coordinate system for all
nodes. Our system is thus easy to define recursively and lends itself to
parallelization. It also guarantees that layouts have many nice properties,
such as: it guarantees certain edges never cross during an animation.
We compared the layouts and transitions produced by our algorithms to those
produced by Yee et al. Results from several experiments indicate that our
system produces fewer edge crossings during transitions between graph drawings,
and that the transitions more often involve changes in local scaling rather
than structure.
These findings suggest the system has promise as an interactive graph
exploration tool in a variety of settings
Leveraging Citation Networks to Visualize Scholarly Influence Over Time
Assessing the influence of a scholar's work is an important task for funding
organizations, academic departments, and researchers. Common methods, such as
measures of citation counts, can ignore much of the nuance and
multidimensionality of scholarly influence. We present an approach for
generating dynamic visualizations of scholars' careers. This approach uses an
animated node-link diagram showing the citation network accumulated around the
researcher over the course of the career in concert with key indicators,
highlighting influence both within and across fields. We developed our design
in collaboration with one funding organization---the Pew Biomedical Scholars
program---but the methods are generalizable to visualizations of scholarly
influence. We applied the design method to the Microsoft Academic Graph, which
includes more than 120 million publications. We validate our abstractions
throughout the process through collaboration with the Pew Biomedical Scholars
program officers and summative evaluations with their scholars
AMADA-Analysis of Multidimensional Astronomical Datasets
We present AMADA, an interactive web application to analyse multidimensional
datasets. The user uploads a simple ASCII file and AMADA performs a number of
exploratory analysis together with contemporary visualizations diagnostics. The
package performs a hierarchical clustering in the parameter space, and the user
can choose among linear, monotonic or non-linear correlation analysis. AMADA
provides a number of clustering visualization diagnostics such as heatmaps,
dendrograms, chord diagrams, and graphs. In addition, AMADA has the option to
run a standard or robust principal components analysis, displaying the results
as polar bar plots. The code is written in R and the web interface was created
using the Shiny framework. AMADA source-code is freely available at
https://goo.gl/KeSPue, and the shiny-app at http://goo.gl/UTnU7I.Comment: Accepted for publication in Astronomy & Computin
- …