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  • 引言
  • Graph types
  • Algorithms
    • Approximations and Heuristics
    • Assortativity
    • Asteroidal
    • Bipartite
    • Boundary
    • Bridges
    • Broadcasting
    • Centrality
    • Chains
    • Chordal
    • Clique
    • Clustering
    • Coloring
    • Communicability
    • Communities
    • Components
    • Connectivity
    • Cores
    • Covering
    • Cycles
    • Cuts
    • D-Separation
    • Directed Acyclic Graphs
    • Distance Measures
    • Distance-Regular Graphs
    • Dominance
    • Dominating Sets
    • Efficiency
    • Eulerian
    • Flows
    • Graph Hashing
    • Graphical degree sequence
    • Hierarchy
    • Hybrid
    • Isolates
    • Isomorphism
    • Link Analysis
    • Link Prediction
    • Lowest Common Ancestor
    • Matching
    • Minors
    • Maximal independent set
    • non-randomness
    • Moral
    • Node Classification
    • Operators
    • Planarity
    • Planar Drawing
    • Graph Polynomials
    • Reciprocity
    • Regular
    • Rich Club
    • Shortest Paths
    • Similarity Measures
    • Simple Paths
    • Small-world
    • s metric
    • Sparsifiers
    • Structural holes
    • Summarization
    • Swap
    • Threshold Graphs
    • Time dependent
    • Tournament
    • Traversal
    • Tree
    • Triads
    • Vitality
    • Voronoi cells
    • Walks
    • Wiener Index
  • Functions
  • Graph generators
  • Linear algebra
  • Converting to and from other data formats
  • Relabeling nodes
  • Reading and writing graphs
  • Drawing
  • 随机性
  • Exceptions
  • Utilities
  • 后端和配置
  • 术语表
  • Reference
  • Algorithms
  • Link Prediction

Link Prediction#

链接预测算法。

resource_allocation_index(G[, ebunch])

计算ebunch中所有节点对的资源分配指数。

jaccard_coefficient(G[, ebunch])

计算ebunch中所有节点对的Jaccard系数。

adamic_adar_index(G[, ebunch])

计算ebunch中所有节点对的Adamic-Adar指数。

preferential_attachment(G[, ebunch])

计算ebunch中所有节点对的优先连接得分。

cn_soundarajan_hopcroft(G[, ebunch, community])

计算ebunch中所有节点对的共同邻居数量,使用社区信息。

ra_index_soundarajan_hopcroft(G[, ebunch, ...])

计算ebunch中所有节点对的资源分配指数,使用社区信息。

within_inter_cluster(G[, ebunch, delta, ...])

计算ebunch中所有节点对的类内和类间共同邻居的比率。

common_neighbor_centrality(G[, ebunch, alpha])

返回每对节点的CCPA分数。

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