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TE_PC.zip (12.8 MB)
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| Name | Modified | Size | Downloads / Week |
|---|---|---|---|
| temp_output_kLayers.txt | 2024-10-30 | 1.5 MB | |
| pre_proc_data.cpp | 2024-10-30 | 9.3 kB | |
| sdb_pred.cpp | 2024-10-30 | 47.1 kB | |
| cluster-details.cpp | 2024-10-30 | 13.8 kB | |
| PC_matrix.txt | 2024-10-30 | 4.2 kB | |
| README.md | 2024-10-30 | 686 Bytes | |
| K-sparsified-graph.pdf | 2024-10-30 | 30.3 kB | |
| layer-wise-connection.pdf | 2024-10-30 | 38.1 kB | |
| TE_PC.zip | 2024-10-30 | 12.8 MB | |
| Totals: 9 Items | 14.5 MB | 0 |
So-Connect
Predict layer-wise connections in social networks
Steps to run the codes related to the project.
a) Initially process the P X C matrix as a (n x 5) dimension dataset.
b) After that prepare the "sdb_pred.cpp" code is prepared for execution.
c) The SNN, KNN, DENSITY values are taken as command line arguments to the "sdb_pred.cpp" code.
d) The <sdb_pred.cpp> code is executed thereafter. The clustering results which are obtained are fed to the <cluster-details.cpp> code.
e) The <cluster-details.cpp> is executed with Cluster-global.bin file as input. Once the code is run, the clusters, outliers, layers and all other necessary information are produced.
