Exploring Sampling Techniques in Large Graphs and Networks

It explores and introduces a classification system for existing sampling methods, calculates the probability of node selection in each graph, and finally ...

[PDF] Exploring Sampling Techniques in Large Graphs and Networks

A new sampling technique is proposed, Spontaneous Forest Fire Sampling (SFFS), which has been modiﬁed from FFS and found that depending on sampling goals, ...

Sampling from Large Graphs - Stanford Computer Science

Exploration methods match the clustering coefficient. For temporal graph patterns in table 1 we see that RW performs best. This means that properties of sample ...

Visualization-Driven Graph Sampling Strategy for Exploring Large ...

Graph sampling is crucial for analyzing and understanding large-scale networks across various domains. While numerous approaches have been ...

Context-aware Sampling of Large Networks via Graph ... - IEEE Xplore

In this paper, a new graph sampling method is proposed oriented to the preservation of contextual structures.

Inclusive random sampling in graphs and networks

The superiority of the sampling method is often attributed to Scott Feld's friendship paradox (Feld 1991), the network phenomenon that the ...

Sampling Techniques for Large, Dynamic Graphs

In our ongoing work, we are adding other types of random graphs, such as certain power-law random graphs and small-world graphs, to explore the robustness of ...

Sampling Multiple Nodes in Large Networks:Beyond Random Walks

perspective on social networks [46]. We start by exploring the graph with a random walk that is biased towards higher degree nodes. With the ...

Sampling unknown large networks restricted by low sampling rates

Graph sampling plays an important role in data mining for large networks. Specifically, larger networks often correspond to lower sampling ...

A Survey of Large Graph Sampling Techniques - SciEngine

As a common method for simplifying network graphs, large graph sampling can reduce the size of large graph data significantly. In this paper, related works ...

Visualization-Driven Graph Sampling Strategy for Exploring Large ...

Graph sampling is crucial for analyzing and understanding large-scale networks across various domains. While numerous approaches have been proposed in the ...

Sampling from Large Graphs with a Reservoir - IEEE Xplore

As a result, graph sampling via crawling, in particular, random walk based graph sampling methods (or Markov chain samplers) become the feasible approach to ...

Sampling from a huge graph in networkx - python 2.7 - Stack Overflow

do you know whether networkx allows a subgraph method like this where I pass it the edges I want to keep? I need to take a subgraph of a graph ...

Cluster-preserving sampling algorithm for large-scale graphs

Graph sampling is a very effective method to deal with scalability issues when analyzing large-scale graphs. Lots of sampling algorithms ...

Sampling from large graphs | Request PDF - ResearchGate

The traversal-based samplings [5] are time efficient, which enables complex mining algorithms, such as graph convolutional networks [1] , ...

Spikyball Sampling: Exploring Large Networks via - ProQuest

Related Work. There are two main families of graph sampling methods adopting a neighbor exploration strategy. The first family is based on random walks (RWs) ...

A Fast Sampling Method of Exploring Graphlet Degrees of Large ...

Title:A Fast Sampling Method of Exploring Graphlet Degrees of Large Directed and Undirected Graphs ; Subjects: Social and Information Networks ( ...

Mosar: Efficiently Characterizing Both Frequent and Rare Motifs in ...

Due to high computational costs, exploring motif statistics (such as motif frequencies) of a large graph can be challenging.

A subgraph sampling method for training large-scale graph ...

Since GCN updates nodes with a recursive neighbor aggregation scheme, training GCN on large-scale graphs suffers from enormous computational cost and large ...

Network Sampling via Edge-based Node Selection with Graph ...

We first present a background on sampling methods in Section 2. Next, we out- line our proposed sampling algorithm, TIES, explore its properties analytically, ...