Readme output added.

README.md

@@ -1,5 +1,10 @@
-## Project No. 1: <hr>
+All the codes, readme, and results is available in the link [Github Link](https://github.com/sraashis/graph-de-anonymization)
+
+### Install libraries:
+ - pip install -U numpy networkx tqdm torch pandas scikit-learn matplotlib
+### ***Final results are in the output folder*** 
 
+## Project No. 1: <hr>
 ### This is the implementation of graph de-anonymization in two ways:
 - **Seed Based**   
     - It includes iterative seed propagation technique by matching multi-hop neighborhood structure
@@ -8,7 +13,6 @@
 
 ### Usage for seed-based
     - python seed_based_main.py -nw 32 -g1 seedbased/G1.edgelist -g2 seedbased/G2.edgelist -sm seedbased/seed_node_pairs.txt -out seedbased/seed_based_result.txt
-### ***Final result is in output folder*** 
 ```commandline
   -nw NUM_WORKERS, --num_workers Number of workers/processes.
   -g1 G1_EDGELIST_FILE, --g1_edgelist_file, Path to g1 edgelist.
@@ -38,4 +42,5 @@ chmod x+u jobs.sh
 ./jobs.sh
 ```
 
-### Question No 2: <hr>
+### Project No 2: <hr>
+### The implementation is in AdultDataset.ipynb python notebook.