This project consists of two main components:

1. Frontend: A React application that provides an interface for searching and visualizing data from an intranet.
2. Backend: A Quarkus-based application running on an Azure Virtual Machine (VM) that powers the API and handles data processing. The webserver runs in a nginx docker.

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Live Preview

You have to allow unsafe connections (click on the https symbol and deactivate it)

Features

• Intranet Search: Search across 260 intranet pages

• Search Modes:

  • tdidf score
  • cosine similarity
  • cosine similarity + pagerank

• Graph Visualization: Display relationships between intranet pages in an interactive graph.

  • hover node to highlight all links
  • click node to see tokens with tf-score
  • circular mode
  • force mode

• PageRank and TF Score Visualization: Visualize page ranking and term frequency scores.

The content of the sites is very basic and the site has no real use. The sites contain a lot of content about cheeses so use corresponding queries.

Running backend

1. Clone repository

git clone https://github.com/Sim-sat/searchBackEnd.git
cd searchBackEnd

2. Start nginx docker

cd webserver
docker compose up -d

3. Build Quarkus project using uber-jar

mvn clean package

4. Run Quarkus project

java -jar target/searchenginequarkus-1.0-SNAPSHOT-runner.jar

The uber jar can run anywhere it just need the nginx server

Running Frontend

Prerequisites

• Node.js (v16 or later)
• npm

Setup

1. Start backend
2. Clone the repository:

   git clone (https://github.com/Sim-sat/searchFrontEnd.git)
   cd searchFrontEnd

3. Install dependencies:

   npm install

4. Start the development server:

   npm start

5. Access the application at http://localhost:5173.

Build

To create a production build:

npm run build