Abstract: Techniques are provided for determining which entities, in a population of entities, is most like a given entity. In the context of companies, the techniques involve constructing a peer network graph based on company-to-company relationship data. Once the graph is constructed, the weights of the edges are determined, and values for the paths are determined based on the edge weights. Peer connection scores are generated for a particular company based on the number and values of the paths between the node that represents the company and the nodes that represent other companies. Based on the peer connection scores between the particular company and other companies, a subset of the other companies are selected as members of a peer group for the company.

Abstract: Techniques are provided for determining which entities, in a population of entities, is most like a given entity. In the context of companies, the techniques involve constructing a peer network graph based on company-to-company relationship data. Once the graph is constructed, the weights of the edges are determined, and values for the paths are determined based on the edge weights. Peer connection scores are generated for a particular company based on the number and values of the paths between the node that represents the company and the nodes that represent other companies. Based on the peer connection scores between the particular company and other companies, a subset of the other companies are selected as members of a peer group for the company.