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v4.3
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    v4.3

      Common Neighbors

      ✓ File Writeback ✕ Property Writeback ✓ Direct Return ✓ Stream Return ✕ Stats

      The Topological Link Prediction algorithm employs various metrics to assess the similarity between pairs of nodes, leveraging the topological attributes of nodes. A higher similarity score implies a greater likelihood of future connectivity between two nodes (which are not connected yet).

      Overview

      The Common Neighbors algorithm computes the number of common neighbors between two nodes as a measure of their similarity.

      The logic behind this algorithm is that if two nodes have a high number of neighbors in common, they are likely to be similar or connected in some meaningful way. It is computed using the following formula:

      where N(x) and N(y) are the sets of adjacent nodes to nodes x and y respectively.

      More common neighbors indicate greater similarity between nodes, while a number of 0 indicates no similarity between two nodes.

      In this example, CN(D,E) = |N(D) ∩ N(E)| = |{B, F}| = 2.

      Considerations

      • The Common Neighbors algorithm ignores the direction of edges but calculates them as undirected edges.

      Syntax

      • Command: algo(topological_link_prediction)
      • Parameters:
      Name
      Type
      Spec
      Default
      Optional
      Description
      ids / uuids []_id / []_uuid / / No ID/UUID of the first set of nodes to calculate; each node in ids/uuids will be paired with each node in ids2/uuids2
      ids2 / uuids2 []_id / []_uuid / / No ID/UUID of the second set of nodes to calculate; each node in ids/uuids will be paired with each node in ids2/uuids2
      type string Common_Neighbors Adamic_Adar No Type of similarity; for Common Neighbors, keep it as Common_Neighbors
      limit int >=-1 -1 Yes Number of results to return, -1 to return all results

      Example

      The example graph is as follows:

      File Writeback

      Spec Content
      filename node1,node2,num
      algo(topological_link_prediction).params({
        uuids: [3],
        uuids2: [1,5,7],
        type: 'Common_Neighbors'
      }).write({
        file:{ 
          filename: 'cn'
        }
      })
      

      Results: File cn

      C,A,1.000000
      C,E,2.000000
      C,G,1.000000
      

      Direct Return

      Alias Ordinal Type
      Description
      Columns
      0 []perNodePair Node pair and its similarity node1, node2, num
      algo(topological_link_prediction).params({
        ids: 'C',
        ids2: ['A','C','E','G'],
        type: 'Common_Neighbors'
      }) as cn 
      return cn 
      

      Results: cn

      node1 node2 num
      3 1 1
      3 5 2
      3 7 1

      Stream Return

      Alias Ordinal Type
      Description
      Columns
      0 []perNodePair Node pair and its similarity node1, node2, num
      find().nodes() as n
      with collect(n._id) as nID
      algo(topological_link_prediction).params({
        ids: 'C',
        ids2: nID,
        type: 'Common_Neighbors'
      }).stream() as cn
      where cn.num >= 2
      return cn
      

      Results: cn

      node1 node2 num
      3 4 2
      3 5 2
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