International Workshop on High Performance Big Graph Data Management, Analysis, and Mining

摘要截稿:

全文截稿: 2018-10-19

开会时间: 2019-12-10

会议难度:

CCF分类: 无

会议地点: Seattle, WA, USA

Overview

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 streams
Representation Learning for graph data
Computational methods for visualization of large-scale graphs
Deep Learning based models for learning on graph data
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