Ecosyste.ms: Repos
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GitHub topics: lfr-benchmark
ytabatabaee/CM-LFR-analysis
Synthetic datasets for analysing Connectivity Modifier (CM)
Language: Python - Size: 8.91 MB - Last synced: 4 months ago - Pushed: 4 months ago - Stars: 0 - Forks: 0
RapidsAtHKUST/SyntheticGraphBenchmark
Synthetic Graph Generator (LFR Benchmark, 2009)
Language: C++ - Size: 3.48 MB - Last synced: 7 months ago - Pushed: over 6 years ago - Stars: 1 - Forks: 1
ytabatabaee/emulate-real-nets
Emulating real networks and clusterings using LFR graphs
Language: Python - Size: 4.91 MB - Last synced: 2 months ago - Pushed: 2 months ago - Stars: 1 - Forks: 0
skaraoglu/Community-Detection-on-Graphs-with-Multiple-Layered-Community-Structure
This project focuses on the community structure analysis on graphs with multiple layers of community structures embedded in it. To conduct experiments on multiple layers of community structures in the graph, graphs that are based on the same nodes but wired with different edges are merged. Then the merged graph is analyzed by different techniques - such as community detection algorithms, overlapping community detection algorithms, nested community detection algorithms - to recover information about community structures set in the merged graph.
Language: Jupyter Notebook - Size: 14.4 MB - Last synced: about 1 year ago - Pushed: over 3 years ago - Stars: 1 - Forks: 0
skaraoglu/Community-Detection-of-Superimposed-Relational-Structures
Algorithms for “community” or cohesive subgraph detection are frequently used to analyze network representations of complex systems, and constitute an active area of methodological research. Algorithms for overlapping community detection are of particular interest, because it is often unrealistic to form strict partitions of natural systems, with at least some nodes participating in multiple clusters. However, the literature on overlapping communities does not distinguish different sources of potential overlap. This paper begins by discussing randomness, bridging nodes, and superimposed relational structures as three distinct sources of overlapping communities. It then focuses on the third source (neglected in the literature), by constructing test graphs that merge two distinct relational structures and comparing the communities identified by eight partition and overlapping community algorithms. Results show that most algorithms focus on the same source structure in each graph, ignoring the other, although a few algorithms find combined or nested communities from both structures.
Size: 1.59 MB - Last synced: about 1 year ago - Pushed: over 2 years ago - Stars: 0 - Forks: 0