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nightly (25.12)
nightly (25.12)stable (25.10)legacy (25.08)
  • Basics
  • nx-cugraph
  • Installation
  • Tutorials
  • Graph Support
  • WholeGraph
  • References
  • Developer Resources
  • API Reference
  • GitHub
  • Twitter

Section Navigation

Core Graph API Documentation

  • cugraph API Reference
    • Graph Classes
      • cugraph.Graph
      • cugraph.MultiGraph
      • cugraph.Graph.from_cudf_adjlist
      • cugraph.Graph.from_cudf_edgelist
      • cugraph.Graph.from_dask_cudf_edgelist
      • cugraph.Graph.from_pandas_adjacency
      • cugraph.Graph.from_pandas_edgelist
      • cugraph.Graph.from_numpy_array
      • cugraph.Graph.from_numpy_matrix
      • cugraph.Graph.add_internal_vertex_id
      • cugraph.Graph.add_nodes_from
      • cugraph.Graph.clear
      • cugraph.Graph.unrenumber
      • cugraph.symmetrize
      • cugraph.symmetrize_ddf
      • cugraph.symmetrize_df
      • cugraph.from_adjlist
      • cugraph.from_cudf_edgelist
      • cugraph.from_edgelist
      • cugraph.from_numpy_array
      • cugraph.from_numpy_matrix
      • cugraph.from_pandas_adjacency
      • cugraph.from_pandas_edgelist
      • cugraph.to_numpy_array
      • cugraph.to_numpy_matrix
      • cugraph.to_pandas_adjacency
      • cugraph.to_pandas_edgelist
      • cugraph.structure.NumberMap
      • cugraph.structure.NumberMap.from_internal_vertex_id
      • cugraph.structure.NumberMap.to_internal_vertex_id
      • cugraph.structure.NumberMap.add_internal_vertex_id
      • cugraph.structure.NumberMap.compute_vals
      • cugraph.structure.NumberMap.compute_vals_types
      • cugraph.structure.NumberMap.generate_unused_column_name
      • cugraph.structure.NumberMap.renumber
      • cugraph.structure.NumberMap.renumber_and_segment
      • cugraph.structure.NumberMap.set_renumbered_col_names
      • cugraph.structure.NumberMap.unrenumber
      • cugraph.structure.NumberMap.vertex_column_size
      • cugraph.hypergraph
    • Graph Implementation
      • cugraph.structure.graph_implementation.simpleGraphImpl.view_edge_list
      • cugraph.structure.graph_implementation.simpleGraphImpl.delete_edge_list
      • cugraph.structure.graph_implementation.simpleGraphImpl.view_adj_list
      • cugraph.structure.graph_implementation.simpleGraphImpl.view_transposed_adj_list
      • cugraph.structure.graph_implementation.simpleGraphImpl.delete_adj_list
      • cugraph.structure.graph_implementation.simpleGraphImpl.enable_batch
      • cugraph.structure.graph_implementation.simpleGraphImpl.get_two_hop_neighbors
      • cugraph.structure.graph_implementation.simpleGraphImpl.number_of_vertices
      • cugraph.structure.graph_implementation.simpleGraphImpl.number_of_nodes
      • cugraph.structure.graph_implementation.simpleGraphImpl.number_of_edges
      • cugraph.structure.graph_implementation.simpleGraphImpl.in_degree
      • cugraph.structure.graph_implementation.simpleGraphImpl.out_degree
      • cugraph.structure.graph_implementation.simpleGraphImpl.degree
      • cugraph.structure.graph_implementation.simpleGraphImpl.degrees
      • cugraph.structure.graph_implementation.simpleGraphImpl.has_edge
      • cugraph.structure.graph_implementation.simpleGraphImpl.has_node
      • cugraph.structure.graph_implementation.simpleGraphImpl.has_self_loop
      • cugraph.structure.graph_implementation.simpleGraphImpl.edges
      • cugraph.structure.graph_implementation.simpleGraphImpl.nodes
      • cugraph.structure.graph_implementation.simpleGraphImpl.neighbors
      • cugraph.structure.graph_implementation.simpleGraphImpl.vertex_column_size
    • Property Graph
      • cugraph.experimental.PropertySelection
      • cugraph.experimental.PropertyGraph
      • cugraph.experimental.PropertyGraph.add_edge_data
      • cugraph.experimental.PropertyGraph.add_vertex_data
      • cugraph.experimental.PropertyGraph.annotate_dataframe
      • cugraph.experimental.PropertyGraph.edge_props_to_graph
      • cugraph.experimental.PropertyGraph.extract_subgraph
      • cugraph.experimental.PropertyGraph.get_edge_data
      • cugraph.experimental.PropertyGraph.get_num_edges
      • cugraph.experimental.PropertyGraph.get_num_vertices
      • cugraph.experimental.PropertyGraph.get_vertex_data
      • cugraph.experimental.PropertyGraph.get_vertices
      • cugraph.experimental.PropertyGraph.has_duplicate_edges
      • cugraph.experimental.PropertyGraph.is_multigraph
      • cugraph.experimental.PropertyGraph.renumber_edges_by_type
      • cugraph.experimental.PropertyGraph.renumber_vertices_by_type
      • cugraph.experimental.PropertyGraph.select_edges
      • cugraph.experimental.PropertyGraph.select_vertices
    • Centrality
      • cugraph.centrality.betweenness_centrality
      • cugraph.centrality.edge_betweenness_centrality
      • cugraph.dask.centrality.betweenness_centrality.betweenness_centrality
      • cugraph.dask.centrality.betweenness_centrality.edge_betweenness_centrality
      • cugraph.centrality.katz_centrality
      • cugraph.dask.centrality.katz_centrality.katz_centrality
      • cugraph.centrality.degree_centrality
      • cugraph.centrality.eigenvector_centrality
      • cugraph.dask.centrality.eigenvector_centrality.eigenvector_centrality
    • Community
      • cugraph.ego_graph
      • cugraph.dask.community.egonet
      • cugraph.ecg
      • cugraph.dask.community.ecg.ecg
      • cugraph.k_truss
      • cugraph.ktruss_subgraph
      • cugraph.dask.community.ktruss_subgraph.ktruss_subgraph
      • cugraph.leiden
      • cugraph.dask.community.leiden.leiden
      • cugraph.dask.community.leiden.leiden
      • cugraph.louvain
      • cugraph.dask.community.louvain.louvain
      • cugraph.analyzeClustering_edge_cut
      • cugraph.analyzeClustering_modularity
      • cugraph.analyzeClustering_ratio_cut
      • cugraph.spectralBalancedCutClustering
      • cugraph.spectralModularityMaximizationClustering
      • cugraph.induced_subgraph
      • cugraph.dask.community.induced_subgraph.induced_subgraph
      • cugraph.triangle_count
      • cugraph.dask.community.triangle_count.triangle_count
    • Components
      • cugraph.connected_components
      • cugraph.strongly_connected_components
      • cugraph.weakly_connected_components
      • cugraph.dask.components.connectivity.weakly_connected_components
    • Cores
      • cugraph.core_number
      • cugraph.dask.cores.core_number.core_number
      • cugraph.k_core
      • cugraph.dask.cores.k_core.k_core
    • Layout
      • cugraph.force_atlas2
    • Linear Assignment
      • cugraph.hungarian
      • cugraph.dense_hungarian
    • Link Analysis
      • cugraph.hits
      • cugraph.dask.link_analysis.hits.hits
      • cugraph.pagerank
      • cugraph.dask.link_analysis.pagerank.pagerank
    • Link Prediction
      • cugraph.cosine
      • cugraph.link_prediction.cosine
      • cugraph.jaccard
      • cugraph.jaccard_coefficient
      • cugraph.overlap
      • cugraph.overlap_coefficient
      • cugraph.dask.link_prediction.overlap.overlap
      • cugraph.sorensen
      • cugraph.sorensen_coefficient
      • cugraph.dask.link_prediction.sorensen.sorensen
    • Sampling
      • cugraph.biased_random_walks
      • cugraph.heterogeneous_neighbor_sample
      • cugraph.homogeneous_neighbor_sample
      • cugraph.uniform_neighbor_sample
      • cugraph.dask.sampling.biased_random_walks.biased_random_walks
      • cugraph.dask.sampling.random_walks.random_walks
      • cugraph.dask.sampling.uniform_neighbor_sample.uniform_neighbor_sample
      • cugraph.dask.sampling.uniform_random_walks.uniform_random_walks
      • cugraph.dask.sampling.node2vec_random_walks.node2vec_random_walks
    • Traversal
      • cugraph.bfs
      • cugraph.bfs_edges
      • cugraph.dask.traversal.bfs.bfs
      • cugraph.filter_unreachable
      • cugraph.shortest_path
      • cugraph.shortest_path_length
      • cugraph.sssp
      • cugraph.dask.traversal.sssp.sssp
    • Tree
      • cugraph.tree.minimum_spanning_tree.minimum_spanning_tree
      • cugraph.tree.minimum_spanning_tree.maximum_spanning_tree
    • Generators
      • cugraph.generators.rmat
    • DASK MG Helper functions
      • cugraph.dask.comms.comms.initialize
      • cugraph.dask.comms.comms.destroy
      • cugraph.dask.comms.comms.is_initialized
      • cugraph.dask.comms.comms.get_comms
      • cugraph.dask.comms.comms.get_workers
      • cugraph.dask.comms.comms.get_session_id
      • cugraph.dask.comms.comms.get_2D_partition
      • cugraph.dask.comms.comms.get_default_handle
      • cugraph.dask.comms.comms.get_handle
      • cugraph.dask.comms.comms.get_worker_id
      • cugraph.dask.common.read_utils.get_chunksize
    • Multi-GPU with cuGraph
  • pylibcugraph API reference
    • pylibcugraph.eigenvector_centrality
    • pylibcugraph.katz_centrality
    • pylibcugraph.strongly_connected_components
    • pylibcugraph.weakly_connected_components
    • pylibcugraph.pagerank
    • pylibcugraph.hits
    • pylibcugraph.bfs
    • pylibcugraph.sssp
  • cuGraph C API documentation
    • Centrality
    • Community
    • Core
    • Components
    • Sampling
    • Similarity
    • Traversal
  • cuGraph C++ API
    • Algorithmns
      • Centrality
      • Community
      • Sampling
      • Similarity
      • Traversal
      • Linear
      • Link Analysis
      • Layout
      • Tree
      • Utility Functions
    • Graph Functions
    • Graph Generators
    • Legacy Graph Functions
    • Sampling Functions
    • Collection Wrappers
    • Low Level cuGraph C++ API

Graph Neural Networks API Documentation

  • cugraph-pyg API Reference
    • cugraph_pyg.data.graph_store.GraphStore
    • cugraph_pyg.data.feature_store.FeatureStore
    • cugraph_pyg.loader.node_loader.NodeLoader
    • cugraph_pyg.loader.neighbor_loader.NeighborLoader
    • cugraph_pyg.loader.link_loader.LinkLoader
    • cugraph_pyg.loader.link_neighbor_loader.LinkNeighborLoader
    • cugraph_pyg.sampler.sampler.BaseSampler
    • cugraph_pyg.sampler.sampler.SampleReader
    • cugraph_pyg.sampler.sampler.HomogeneousSampleReader
    • cugraph_pyg.sampler.sampler.HeterogeneousSampleReader
    • cugraph_pyg.sampler.sampler.SampleIterator
    • cugraph_pyg.sampler.distributed_sampler.BaseDistributedSampler
    • cugraph_pyg.sampler.distributed_sampler.DistributedNeighborSampler

Additional Graph Packages API Documentation

  • cugraph-service API Reference
    • cugraph-service-client API Reference
    • cugraph-service-server API Reference
  • API Reference
  • cugraph API Reference
  • Link Prediction
  • cugraph.dask.link_prediction.overlap.overlap

cugraph.dask.link_prediction.overlap.overlap#

cugraph.dask.link_prediction.overlap.overlap(input_graph, vertex_pair=None, use_weight=False)[source]#

Compute the Overlap Coefficient between each pair of vertices connected by an edge, or between arbitrary pairs of vertices specified by the user. Overlap Coefficient is defined between two sets as the ratio of the volume of their intersection over the smaller of their two volumes. In the context of graphs, the neighborhood of a vertex is seen as a set. The Overlap Coefficient weight of each edge represents the strength of connection between vertices based on the relative similarity of their neighbors. If first is specified but second is not, or vice versa, an exception will be thrown.

cugraph.overlap, in the absence of a specified vertex pair list, will compute the two_hop_neighbors of the entire graph to construct a vertex pair list and will return the Overlap coefficient for those vertex pairs. This is not advisable as the vertex_pairs can grow exponentially with respect to the size of the datasets

Parameters:
input_graphcugraph.Graph

cuGraph Graph instance, should contain the connectivity information as an edge list (edge weights are not supported yet for this algorithm). The graph should be undirected where an undirected edge is represented by a directed edge in both direction. The adjacency list will be computed if not already present.

This implementation only supports undirected, non-multi Graphs.

vertex_paircudf.DataFrame, optional (default=None)

A GPU dataframe consisting of two columns representing pairs of vertices. If provided, the Overlap coefficient is computed for the given vertex pairs. If the vertex_pair is not provided then the current implementation computes the Overlap coefficient for all vertices that are two hops apart in the graph.

use_weightbool, optional (default=False)

Flag to indicate whether to compute weighted overlap (if use_weight==True) or un-weighted overlap (if use_weight==False). ‘input_graph’ must be weighted if ‘use_weight=True’.

Returns:
resultdask_cudf.DataFrame

GPU distributed data frame containing 3 dask_cudf.Series

ddf[‘first’]: dask_cudf.Series

The first vertex ID of each pair(will be identical to first if specified).

ddf[‘second’]: dask_cudf.Series

The second vertex ID of each pair(will be identical to second if specified).

ddf[‘overlap_coeff’]: dask_cudf.Series

The computed overlap coefficient between the first and the second vertex ID.

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