CFP: SDM 2014 Workshop on Mining Networks and Graphs: A Big Data Analytic Challenge

"Pinar, Ali" <[email protected]> Tue, 7 Jan 2014 01:34:17 +0000
Newsgroups gmane.comp.mathematics.csc
Message-ID <CEF09954.141E0%[email protected]>
Reminder:  Deadline is this Friday.

Call for Papers. Submission deadline January 10.

SDM 2014 Workshop on
Mining Networks and Graphs: A Big Data Analytic Challenge
http://staff.vbi.vt.edu/maleq/MNG2014/index.php

April 24-26, 2014, Philadelphia, PA

The Workshop on Mining Networks and Graphs will be held on April 24-26,
2014 in Philadelphia, PA in conjunction with the SIAM International
Conference on Data Mining (SDM 2014)

The workshop is targeted for researchers interested in data mining,
machine learning, massive data analytics, network science, social
networks and high performance computing in its broadest sense. Both
theoreticians as well as practitioners, including system builders and
individuals applying network analytic methods in application domains
will be benefited from this workshop.

Networks are emerging as a common language to model a wide variety of
systems in life sciences, engineering, and social sciences. Real-world
applications give rise to networks that are unstructured and often
comprise of multiple-networks. Furthermore, they support multiple
dynamical processes that shape the network over time. Network science
refers to the broad discipline that seeks to understand the underlying
principles that govern the synthesis, analysis and co-evolution of networks.

The workshop will focus on processing large networks. Such networks can
be directed as well as undirected, they can be labeled or unlabeled or
they can be weighted or unweighted. Furthermore, network of networks is
also of interest. Specific scientific topics of interest to the meeting
include but are not restricted to: mining for patterns of interest in
the networks, efficient exact and approximation algorithms that are
either sequential or parallel for analyzing network properties. Recent
methods for processing large networks such as map-reduce based
frameworks, database techniques for processing networks. A particular
topic of interest is to couple structural properties of networks to the
dynamics over networks, e.g. contagions.


Ali Pinar, [email protected]<mailto:[email protected]>
Sandia National Labs, Livermore, CA 94551-9159
phone: 925-294-4683, fax: 925-294-2234
http://www.sandia.gov/~apinar

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