Resource allocation index: The similarity between x and y can be defined as the amount of resource y received from x.
Jaccard Coefficient: Measures similarity between finite sample sets, and is defined as the size of the intersection divided by the size of the union of the sample sets.
Adamic-Adar Index: This index refines the simple counting of common neighbors by assigning the lowerconnected neighbors more weights.
Preferential Attachment: The mechanism of preferential attachment can be used to generate evolving scale-free networks (i.e., networks with power-law degree distributions), where the probability that a new link is connected to the node x is proportional to k(x)
Resource Allocation - Soundarajan Hopcroft: For two nodes u and v, this function computes the resource allocation index considering only common neighbors belonging to the same community as u and v.
Within Inter Cluster: Considers the sets of their intra-cluster or within-cluster (W) and between-cluster or inter-cluster (IC) common neighbors.
Week 4: Start working on project
Week 5: Start working on basic functions
Week 6: Finish all basic functions
Week 7: Create a visualizer for the project
Week 8: Finish up the code for the problem