Scaling graph neural networks with approximate pagerank
Graph neural networks (GNNs) have emerged as a powerful approach for solving many
network mining tasks. However, learning on large graphs remains a challenge--many …
network mining tasks. However, learning on large graphs remains a challenge--many …
Centrality measures in complex networks: A survey
In complex networks, each node has some unique characteristics that define the importance
of the node based on the given application-specific context. These characteristics can be …
of the node based on the given application-specific context. These characteristics can be …
Efficient Algorithms for Personalized PageRank Computation: A Survey
Personalized PageRank (PPR) is a traditional measure for node proximity on large graphs.
For a pair of nodes and, the PPR value equals the probability that an-discounted random …
For a pair of nodes and, the PPR value equals the probability that an-discounted random …
Topppr: top-k personalized pagerank queries with precision guarantees on large graphs
Personalized PageRank (PPR) is a classic metric that measures the relevance of graph
nodes with respect to a source node. Given a graph G, a source node s, and a parameter k …
nodes with respect to a source node. Given a graph G, a source node s, and a parameter k …
A survey of state management in big data processing systems
The concept of state and its applications vary widely across big data processing systems.
This is evident in both the research literature and existing systems, such as Apache Flink …
This is evident in both the research literature and existing systems, such as Apache Flink …
Unifying the global and local approaches: An efficient power iteration with forward push
Personalized PageRank (PPR) is a critical measure of the importance of a node t to a source
node s in a graph. The Single-Source PPR (SSPPR) query computes the PPR's of all the …
node s in a graph. The Single-Source PPR (SSPPR) query computes the PPR's of all the …
Personalized pagerank to a target node, revisited
Personalized PageRank (PPR) is a widely used node proximity measure in graph mining
and network analysis. Given a source node s and a target node t, the PPR value π (s, t) …
and network analysis. Given a source node s and a target node t, the PPR value π (s, t) …
Realtime top-k personalized pagerank over large graphs on gpus
Given a graph G, a source node s∈ G and a positive integer k, a top-k Personalized
PageRank (PPR) query returns the k nodes with the highest PPR values with respect to s …
PageRank (PPR) query returns the k nodes with the highest PPR values with respect to s …
Distributed PageRank computation with improved round complexities
PageRank is a classic measure that effectively evaluates the importance of nodes in large
graphs. It has been applied in numerous applications spanning data mining, Web …
graphs. It has been applied in numerous applications spanning data mining, Web …
[PDF][PDF] Is pagerank all you need for scalable graph neural networks
Graph neural networks (GNNs) have emerged as a powerful approach for solving many
network mining tasks. However, efficiently utilizing them on web-scale data remains a …
network mining tasks. However, efficiently utilizing them on web-scale data remains a …