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BigGraphs 2015 : The Second International Workshop on High Performance Big Graph Data Management, Analysis, and Mining (BigGraphs 2015)


When Oct 29, 2015 - Nov 1, 2015
Where Santa Clara, CA, USA
Submission Deadline Sep 5, 2015
Notification Due Sep 25, 2015
Final Version Due Oct 5, 2015
Categories    computer science   parallel computing   data mining   high performance computing

Call For Papers

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The Second International Workshop on High Performance
Big Graph Data Management, Analysis, and Mining (BigGraphs 2015)

To be held in conjunction with IEEE BigData 2015
Oct 29--Nov 1, 2015, Santa Clara, CA, USA.


Important Dates:
Sep 5, 2015: Due date for workshop papers submission
Sep 25, 2015: Notification of paper acceptance to authors
Oct 5, 2015: Camera-ready of accepted papers

Call for papers:
Modern Big Data increasingly appears in the form of complex graphs and networks.
Examples include the physical Internet, the world wide web, online social networks,
phone networks, and biological networks. In addition to their massive sizes, these
graphs are dynamic, noisy, and sometimes transient. They also conform to all five Vs
(Volume, Velocity, Variety, Value and Veracity) that define Big Data. However, many
graph-related problems are computationally difficult, and thus big graph data brings
unique challenges, as well as numerous opportunities for researchers, to solve various
problems that are significant to our communities. This workshop aims to bring together
researchers from different paradigms solving big graph problems under a unified
platform for sharing their work and exchanging ideas. We are soliciting novel and
original research contributions related to big graph data management, analysis, and
mining (algorithms, software systems, applications, best practices, performance).
Significant work-in-progress papers are also encouraged. Papers can be from any of
the following areas, including but not limited to:
* Parallel algorithms for big graph analysis on HPC systems
* Heterogeneous CPU-GPU solutions to solve big graph problems
* Extreme-scale computing for large graph, tensor, and network problems
* Sampling and summarization of large graphs
* Graph algorithms for large-scale scientific computing problems
* Graph clustering, partitioning, and classification methods
* Scalable graph topology measurement: diameter approximation,
eigenvalues, triangle and graphlet counting
* Parallel algorithms for computing graph kernels
* Inference on large graph data
* Graph evolution and dynamic graph models
* Graph databases, novel querying and indexing strategies for RDF data
* Novel applications of big graph problems in bioinformatics, health care,
security, and social networks
* New software systems and runtime systems for big graph data mining

Submissions must be at most 8 pages long, including all figures, tables, and references.
They must be formatted according to the style files used by the IEEE BigData 2015
conference proceedings. Papers must be submitted online through the workshop submission
page ( by
11.59 pm PDT (Pacific Daylight Time) on September 5, 2015.

Workshop Organizers:
Mohammad Al Hasan
Department of Computer and Information Science
Indiana University-Purdue University Indianapolis
Indianapolis, IN 46202

Kamesh Madduri
Department of Computer Science and Engineering
The Pennsylvania State University
University Park, PA 16802

Fengguang Song
Department of Computer and Information Science
Indiana University-Purdue University Indianapolis
Indianapolis, IN 46202

Program Committee:
Leman Akoglu (Stony Brook University)
Medha Atre (University of Pennsylvania)
Juan Colmenares (Samsung Research America)
Oded Green (Georgia Institute of Technology)
Mahantesh Halappanavar (Pacific Northwest National Laboratory)
Mohammad Al Hasan (Indiana University Purdue University)
Kamesh Madduri (The Pennsylvania State University)
Erik Saule (University of North Carolina at Charlotte)
Fengguang Song (Indiana University Purdue University)
Chen Tian (Huawei Technologies USA)
Stanimire Tomov (University of Tennessee Knoxville)
Mohammed J. Zaki (Rensselaer Polytechnic Institute)

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