Amazon Dataset Analysis

Overview

This project utilizes a dataset obtained from Stanford SNAP. The goal is to implement various graph algorithms, including BFS Distance, Strongly Connected Components, and Pagerank, on the provided dataset.

Video Presentation

Check out our project presentation on YouTube: Project Demo

Building the Code

1. Create Build Directory:

   mkdir build

2. Navigate to Build Directory:

   cd build

3. CMake and Make:

   cmake ..
   make

Running the Code

1. Choose Algorithms:

   • In the main.cpp file, set the boolean variables to true for the algorithms you want to run.

2. Compile and Run:

   • After building, use the following commands in the terminal:

     ./test/

Troubleshooting

1. Changing Input Data Path:

   • Update the test data paths in the tests/tests.cpp file by modifying the relevant variables.

2. Adjusting Algorithm Variables:

   • In the main.cpp file, update the algorithm-specific variables to point to the correct input data paths.

Files Used for Each Function

BFS Distance Algorithm

• main.cpp: Function for Amazon test data.
• tests.cpp: Test cases (testpr2, testpr3, test_data).

Strongly Connected Algorithm

• main.cpp: Test data.
• tests.cpp: Test cases (testpr2, testpr3, test_data).

Pagerank Algorithm

• main.cpp: Function for Amazon test data.
• tests.cpp: Test cases (testpr1, testpr2, testpr3).

Adjacency List

• main.cpp: Function for Amazon test data.
• tests.cpp: Test cases (testpr1, test_data).