74,806 research outputs found
Layered Label Propagation: A MultiResolution Coordinate-Free Ordering for Compressing Social Networks
We continue the line of research on graph compression started with WebGraph,
but we move our focus to the compression of social networks in a proper sense
(e.g., LiveJournal): the approaches that have been used for a long time to
compress web graphs rely on a specific ordering of the nodes (lexicographical
URL ordering) whose extension to general social networks is not trivial. In
this paper, we propose a solution that mixes clusterings and orders, and devise
a new algorithm, called Layered Label Propagation, that builds on previous work
on scalable clustering and can be used to reorder very large graphs (billions
of nodes). Our implementation uses overdecomposition to perform aggressively on
multi-core architecture, making it possible to reorder graphs of more than 600
millions nodes in a few hours. Experiments performed on a wide array of web
graphs and social networks show that combining the order produced by the
proposed algorithm with the WebGraph compression framework provides a major
increase in compression with respect to all currently known techniques, both on
web graphs and on social networks. These improvements make it possible to
analyse in main memory significantly larger graphs
A nonuniform popularity-similarity optimization (nPSO) model to efficiently generate realistic complex networks with communities
The hidden metric space behind complex network topologies is a fervid topic
in current network science and the hyperbolic space is one of the most studied,
because it seems associated to the structural organization of many real complex
systems. The Popularity-Similarity-Optimization (PSO) model simulates how
random geometric graphs grow in the hyperbolic space, reproducing strong
clustering and scale-free degree distribution, however it misses to reproduce
an important feature of real complex networks, which is the community
organization. The Geometrical-Preferential-Attachment (GPA) model was recently
developed to confer to the PSO also a community structure, which is obtained by
forcing different angular regions of the hyperbolic disk to have variable level
of attractiveness. However, the number and size of the communities cannot be
explicitly controlled in the GPA, which is a clear limitation for real
applications. Here, we introduce the nonuniform PSO (nPSO) model that,
differently from GPA, forces heterogeneous angular node attractiveness by
sampling the angular coordinates from a tailored nonuniform probability
distribution, for instance a mixture of Gaussians. The nPSO differs from GPA in
other three aspects: it allows to explicitly fix the number and size of
communities; it allows to tune their mixing property through the network
temperature; it is efficient to generate networks with high clustering. After
several tests we propose the nPSO as a valid and efficient model to generate
networks with communities in the hyperbolic space, which can be adopted as a
realistic benchmark for different tasks such as community detection and link
prediction
De-Trending Time Series for Astronomical Variability Surveys
We present a de-trending algorithm for the removal of trends in time series.
Trends in time series could be caused by various systematic and random noise
sources such as cloud passages, changes of airmass, telescope vibration or CCD
noise. Those trends undermine the intrinsic signals of stars and should be
removed. We determine the trends from subsets of stars that are highly
correlated among themselves. These subsets are selected based on a hierarchical
tree clustering algorithm. A bottom-up merging algorithm based on the departure
from normal distribution in the correlation is developed to identify subsets,
which we call clusters. After identification of clusters, we determine a trend
per cluster by weighted sum of normalized light-curves. We then use quadratic
programming to de-trend all individual light-curves based on these determined
trends. Experimental results with synthetic light-curves containing artificial
trends and events are presented. Results from other de-trending methods are
also compared. The developed algorithm can be applied to time series for trend
removal in both narrow and wide field astronomy.Comment: Revised version according to the referee's second revie
Greedy Forwarding in Dynamic Scale-Free Networks Embedded in Hyperbolic Metric Spaces
We show that complex (scale-free) network topologies naturally emerge from
hyperbolic metric spaces. Hyperbolic geometry facilitates maximally efficient
greedy forwarding in these networks. Greedy forwarding is topology-oblivious.
Nevertheless, greedy packets find their destinations with 100% probability
following almost optimal shortest paths. This remarkable efficiency sustains
even in highly dynamic networks. Our findings suggest that forwarding
information through complex networks, such as the Internet, is possible without
the overhead of existing routing protocols, and may also find practical
applications in overlay networks for tasks such as application-level routing,
information sharing, and data distribution
Adaptive Mesh Refinement for Coupled Elliptic-Hyperbolic Systems
We present a modification to the Berger and Oliger adaptive mesh refinement
algorithm designed to solve systems of coupled, non-linear, hyperbolic and
elliptic partial differential equations. Such systems typically arise during
constrained evolution of the field equations of general relativity. The novel
aspect of this algorithm is a technique of "extrapolation and delayed solution"
used to deal with the non-local nature of the solution of the elliptic
equations, driven by dynamical sources, within the usual Berger and Oliger
time-stepping framework. We show empirical results demonstrating the
effectiveness of this technique in axisymmetric gravitational collapse
simulations. We also describe several other details of the code, including
truncation error estimation using a self-shadow hierarchy, and the
refinement-boundary interpolation operators that are used to help suppress
spurious high-frequency solution components ("noise").Comment: 31 pages, 15 figures; replaced with published versio
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