17.1.7 Computing Similar Vertices for a Vertex Batch
You can fetch the k
most similar vertices for a list of input vertices as described in the following code:
opg4j> var vertices = new ArrayList()
opg4j> vertices.add("Machine_learning")
opg4j> vertices.add("Albert_Einstein")
opg4j> batchedSimilars = model.computeSimilars(vertices, 10)
opg4j> batchedSimilars.print()
List vertices = Arrays.asList("Machine_learning","Albert_Einstein");
PgxFrame batchedSimilars = model.computeSimilars(vertices,10);
batchedSimilars.print();
vertices = ["Machine_learning","Albert_Einstein"]
batched_similars = model.compute_similars(vertices,10)
batched_similars.print()
The following describes the output
result:
+-------------------------------------------------------------------+
| srcVertex | dstVertex | similarity |
+-------------------------------------------------------------------+
| Machine_learning | Machine_learning | 1.0000001192092896 |
| Machine_learning | Data_mining | 0.9070799350738525 |
| Machine_learning | Computer_science | 0.8963605165481567 |
| Machine_learning | Unsupervised_learning | 0.8828719854354858 |
| Machine_learning | R_(programming_language) | 0.8821185827255249 |
| Machine_learning | Algorithm | 0.8819515705108643 |
| Machine_learning | Artificial_neural_network | 0.8773092031478882 |
| Machine_learning | Data_analysis | 0.8758628368377686 |
| Machine_learning | List_of_algorithms | 0.8737979531288147 |
| Machine_learning | K-means_clustering | 0.8715602159500122 |
| Albert_Einstein | Albert_Einstein | 1.0000001192092896 |
| Albert_Einstein | Physics | 0.8664291501045227 |
| Albert_Einstein | Werner_Heisenberg | 0.8625140190124512 |
| Albert_Einstein | Richard_Feynman | 0.8496938943862915 |
| Albert_Einstein | List_of_physicists | 0.8415523767471313 |
| Albert_Einstein | Physicist | 0.8384397625923157 |
| Albert_Einstein | Max_Planck | 0.8370327353477478 |
| Albert_Einstein | Niels_Bohr | 0.8340970873832703 |
| Albert_Einstein | Quantum_mechanics | 0.8331197500228882 |
| Albert_Einstein | Special_relativity | 0.8280861973762512 |
+-------------------------------------------------------------------+
Parent topic: Using the DeepWalk Algorithm