644 research outputs found
Visual Mining of Epidemic Networks
We show how an interactive graph visualization method based on maximal
modularity clustering can be used to explore a large epidemic network. The
visual representation is used to display statistical tests results that expose
the relations between the propagation of HIV in a sexual contact network and
the sexual orientation of the patients.Comment: 8 page
An Interactive Tool to Explore and Improve the Ply Number of Drawings
Given a straight-line drawing of a graph , for every vertex
the ply disk is defined as a disk centered at where the radius of
the disk is half the length of the longest edge incident to . The ply number
of a given drawing is defined as the maximum number of overlapping disks at
some point in . Here we present a tool to explore and evaluate
the ply number for graphs with instant visual feedback for the user. We
evaluate our methods in comparison to an existing ply computation by De Luca et
al. [WALCOM'17]. We are able to reduce the computation time from seconds to
milliseconds for given drawings and thereby contribute to further research on
the ply topic by providing an efficient tool to examine graphs extensively by
user interaction as well as some automatic features to reduce the ply number.Comment: Appears in the Proceedings of the 25th International Symposium on
Graph Drawing and Network Visualization (GD 2017
The Galois Complexity of Graph Drawing: Why Numerical Solutions are Ubiquitous for Force-Directed, Spectral, and Circle Packing Drawings
Many well-known graph drawing techniques, including force directed drawings,
spectral graph layouts, multidimensional scaling, and circle packings, have
algebraic formulations. However, practical methods for producing such drawings
ubiquitously use iterative numerical approximations rather than constructing
and then solving algebraic expressions representing their exact solutions. To
explain this phenomenon, we use Galois theory to show that many variants of
these problems have solutions that cannot be expressed by nested radicals or
nested roots of low-degree polynomials. Hence, such solutions cannot be
computed exactly even in extended computational models that include such
operations.Comment: Graph Drawing 201
Nothing Ventured, Nothing Gained: Addressing the Critical Gaps in Risk-Taking Capital for Social Enterprise
The worldwide growth of social enterprise is threatened by a dearth of capital. Social enterprises need investment to grow and to innovate – investment that takes on the risk of the enterprise. This kind of capital cannot easily be pieced together from limited grants, conventional equity and ill-fitted debt. As increasing numbers of social entrepreneurs and mission-based financiers seek to enter the field, a question arises: Can the sector develop new instruments and stakeholder relationships to meet this challenge
Bayesian modeling of networks in complex business intelligence problems
Complex network data problems are increasingly common in many fields of
application. Our motivation is drawn from strategic marketing studies
monitoring customer choices of specific products, along with co-subscription
networks encoding multiple purchasing behavior. Data are available for several
agencies within the same insurance company, and our goal is to efficiently
exploit co-subscription networks to inform targeted advertising of cross-sell
strategies to currently mono-product customers. We address this goal by
developing a Bayesian hierarchical model, which clusters agencies according to
common mono-product customer choices and co-subscription networks. Within each
cluster, we efficiently model customer behavior via a cluster-dependent mixture
of latent eigenmodels. This formulation provides key information on
mono-product customer choices and multiple purchasing behavior within each
cluster, informing targeted cross-sell strategies. We develop simple algorithms
for tractable inference, and assess performance in simulations and an
application to business intelligence
Drawing Graphs within Restricted Area
We study the problem of selecting a maximum-weight subgraph of a given graph
such that the subgraph can be drawn within a prescribed drawing area subject to
given non-uniform vertex sizes. We develop and analyze heuristics both for the
general (undirected) case and for the use case of (directed) calculation graphs
which are used to analyze the typical mistakes that high school students make
when transforming mathematical expressions in the process of calculating, for
example, sums of fractions
Loan and nonloan flows in the Australian interbank network
High-value transactions between Australian banks are settled in the Reserve
Bank Information and Transfer System (RITS) administered by the Reserve Bank of
Australia. RITS operates on a real-time gross settlement (RTGS) basis and
settles payments sourced from the SWIFT, the Austraclear, and the interbank
transactions entered directly into RITS. In this paper, we analyse a dataset
received from the Reserve Bank of Australia that includes all interbank
transactions settled in RITS on an RTGS basis during five consecutive weekdays
from 19 February 2007 inclusive, a week of relatively quiescent market
conditions. The source, destination, and value of each transaction are known,
which allows us to separate overnight loans from other transactions (nonloans)
and reconstruct monetary flows between banks for every day in our sample. We
conduct a novel analysis of the flow stability and examine the connection
between loan and nonloan flows. Our aim is to understand the underlying causal
mechanism connecting loan and nonloan flows. We find that the imbalances in the
banks' exchange settlement funds resulting from the daily flows of nonloan
transactions are almost exactly counterbalanced by the flows of overnight
loans. The correlation coefficient between loan and nonloan imbalances is about
-0.9 on most days. Some flows that persist over two consecutive days can be
highly variable, but overall the flows are moderately stable in value. The
nonloan network is characterised by a large fraction of persistent flows,
whereas only half of the flows persist over any two consecutive days in the
loan network. Moreover, we observe an unusual degree of coherence between
persistent loan flow values on Tuesday and Wednesday. We probe static
topological properties of the Australian interbank network and find them
consistent with those observed in other countries
Identifying the underlying structure and dynamic interactions in a voting network
We analyse the structure and behaviour of a specific voting network using a
dynamic structure-based methodology which draws on Q-Analysis and social
network theory. Our empirical focus is on the Eurovision Song Contest over a
period of 20 years. For a multicultural contest of this kind, one of the key
questions is how the quality of a song is judged and how voting groups emerge.
We investigate structures that may identify the winner based purely on the
topology of the network. This provides a basic framework to identify what the
characteristics associated with becoming a winner are, and may help to
establish a homogenous criterion for subjective measures such as quality.
Further, we measure the importance of voting cliques, and present a dynamic
model based on a changing multidimensional measure of connectivity in order to
reveal the formation of emerging community structure within the contest.
Finally, we study the dynamic behaviour exhibited by the network in order to
understand the clustering of voting preferences and the relationship between
local and global properties.Comment: 20 pages, 10 figures, 3 tables, submitted to Physica
A Distributed Multilevel Force-directed Algorithm
The wide availability of powerful and inexpensive cloud computing services
naturally motivates the study of distributed graph layout algorithms, able to
scale to very large graphs. Nowadays, to process Big Data, companies are
increasingly relying on PaaS infrastructures rather than buying and maintaining
complex and expensive hardware. So far, only a few examples of basic
force-directed algorithms that work in a distributed environment have been
described. Instead, the design of a distributed multilevel force-directed
algorithm is a much more challenging task, not yet addressed. We present the
first multilevel force-directed algorithm based on a distributed vertex-centric
paradigm, and its implementation on Giraph, a popular platform for distributed
graph algorithms. Experiments show the effectiveness and the scalability of the
approach. Using an inexpensive cloud computing service of Amazon, we draw
graphs with ten million edges in about 60 minutes.Comment: Appears in the Proceedings of the 24th International Symposium on
Graph Drawing and Network Visualization (GD 2016
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