Representation learning on graphs with jum** knowledge networks
Recent deep learning approaches for representation learning on graphs follow a
neighborhood aggregation procedure. We analyze some important properties of these …
neighborhood aggregation procedure. We analyze some important properties of these …
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 …
FORA: simple and effective approximate single-source personalized pagerank
Given a graph G, a source node s and a target node t, the personalized PageRank (PPR) of t
with respect to s is the probability that a random walk starting from s terminates at t. A single …
with respect to s is the probability that a random walk starting from s terminates at t. A single …
When hierarchy meets 2-hop-labeling: Efficient shortest distance queries on road networks
Computing the shortest distance between two vertices is a fundamental problem in road
networks. Since a direct search using the Dijkstra's algorithm results in a large search space …
networks. Since a direct search using the Dijkstra's algorithm results in a large search space …
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 …
Massively parallel algorithms for personalized pagerank
Personalized PageRank (PPR) has wide applications in search engines, social
recommendations, community detection, and so on. Nowadays, graphs are becoming …
recommendations, community detection, and so on. Nowadays, graphs are becoming …
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) …
Hubppr: effective indexing for approximate personalized pagerank
Personalized PageRank (PPR) computation is a fundamental operation in web search,
social networks, and graph analysis. Given a graph G, a source s, and a target t, the PPR …
social networks, and graph analysis. Given a graph G, a source s, and a target t, the PPR …
Personalized pagerank on evolving graphs with an incremental index-update scheme
\em Personalized PageRank (PPR) stands as a fundamental proximity measure in graph
mining. Given an input graph G with the probability of decay α, a source node s and a target …
mining. Given an input graph G with the probability of decay α, a source node s and a target …