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Graph mining - To become a champion

Tyson Mcleod Inglés 10 fichas

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1Degree of a vertexNumber of incident edges
2P(k): probability that a randomly chosen vertex has degree kP(k) = Nk/ N
(Nk = #nodes with degree k)
3The distance between two nodesThe number of edges along the shortest path connecting them
4Betweenness centralityHow many times a node lies on shortest paths between other nodes.
Rationale: "shortest paths = most efficient route to information"
5Clustering coefficient (Triangle-based)Network level:
ratio triangles/ connected triples
6Clustering coefficient (Ego-network-based)Node level:
percentage of edges among neighbors
7Girwan-Newman algorithm1.Calculate betweeness of all edges
2. Remove edge with highest betweeness
3. Recalculate betweeness of edges affected by removal
4. Repeat 2 and 3 until no edges remain
8ModularityClustering quality function
9Clique percolation methodAn approach for analyzing the overlapping community structure of networks.
(networks = clusters = modules)
10Community (community structure)A network is said to have community structure if the nodes of the network can be easily grouped into sets of nodes such that each set of nodes is densely connected internally.