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StructMatrix: large-scale visualization of graphs by means of structure detection and dense matrices
(Institute of Electrical and Electronics Engineers – IEEEAtlantic City, 2015-11)
Given a large-scale graph with millions of nodes and edges, how to reveal macro patterns of interest, like cliques, bi-partite cores, stars, and chains? Furthermore, how to visualize such patterns altogether getting insights ...
An Analysis of Distributed Programming Models and Frameworks for Large-scale Graph Processing
(Taylor & Francis, 2020-04-30)
In recent years, processing and analysing large graphs has become a major need in many research areas. Distributed graph processing programming models and frameworks arised as a natural solution to process linked data of ...
Accelerating Graph Applications Using Phased Transactional Memory
(2021-01-01)
Due to their fine-grained operations and low conflict rates, graph processing algorithms expose a large amount of parallelism that has been extensively exploited by various parallelization frameworks. Transactional Memory ...
An Architecture and Platform for Developing Distributed Recommendation Algorithms on Large-Scale Social Networks
(Sage Publications Ltd, 2015-06)
The creation of new and better recommendation algorithms for social networks is currently receiving much attention owing to the increasing need for new tools to assist users. The volume of available social data as well as ...
DPM: A novel distributed large-scale social graph processing framework for link prediction algorithms
(Elsevier Science, 2018-01)
Large-scale graphs have become ubiquitous in social media. Computer-based recommendations in these huge graphs pose challenges in terms of algorithm design and resource usage efficiency when processing recommendations in ...
Understanding landscape-primary productivity and biodiversity relationship through graph metrics
(2020)
Besides landscape ecological studies, the traditional approach to trying to understand
ecological processes that occur in a landscape is the use of spatial statistics. However,
this does not take into account that many of ...
Node-Depth Encoding and Multiobjective Evolutionary Algorithm Applied to Large-Scale Distribution System Reconfiguration
(IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2010)
The power loss reduction in distribution systems (DSs) is a nonlinear and multiobjective problem. Service restoration in DSs is even computationally hard since it additionally requires a solution in real-time. Both DS ...
Community detection in large-scale networks: a survey and empirical evaluation
(Wiley Online Library, 2016)
A graph-based cache for large-scale similarity search engines
(Springer, 2018-05)
Large-scale similarity search engines are complex systems devised to process unstructured data like images and videos. These systems are deployed on clusters of distributed processors communicated through high-speed networks. ...