/CSC5356_Project_2_SP24

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--------Twitter-Like Recommendation System--------

Project Overview

This project implements a Twitter-like recommendation system. It uses a microservices architecture with a focus on graph-based recommendations. The system suggests hashtags and users to follow based on user tweets and sentiments.

Key Features

  • Post and view tweets.
  • Get recommendations based on user activity and sentiment analysis.
  • Perform sentiment analysis on tweets.
  • Microservices-based architecture for scalability and maintainability.

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

  • Python 3.10
  • Neo4j
  • MongoDB Cloud
  • Kafka
  • NPM
  • React.js / Node.js Framework
  • Apache Spark (for Spark Streaming)
  • Neo4j, Mongo DB Connectors
  • Docker Container

Installation

  1. Clone the repository: git clone https://github.com/elamraniadnane1/Project_3.git
  2. Navigate to the project directory and install the required Python packages: 4.cd Project_3 5.pip install -r requirements.txt

Running the Application

  1. Start the Neo4j and MongoDB databases (in a cloud), and ensure Kafka and Spark Streaming are running and Docker as well.
  2. Install all the requirements
  3. Run the microservices For more details please consult the official report & the video

Usage

  • Access the web application at http://localhost:PORT. The port depend on the local cfg of each user.
  • Post tweets, and view recommendations and sentiment analysis results.

Built With

  • Node.js - The web framework used.
  • React.js - An open-source JavaScript library used for building user interfaces, particularly for single-page applications where you need a fast and interactive user experience. It's maintained by Facebook and a community of individual developers and companies.
  • Neo4j - Graph database.
  • MongoDB - Document database.
  • Kafka - Streaming platform.
  • Spark - Unified analytics engine.

Versioning

We use GitHub for versioning.

Authors

Project Report Outline ( Check our Submissionon on Canvas)

This document provides an outline of the project report, detailing the structure and content of each section. The report is structured into several key sections, each focusing on a different aspect of the project.

Report Structure

  • Project Team

    • Table with team members and their respective roles and contributions.

  • Project Definition

    • Brief description of project goals.
    • Functional and non-functional requirements.
    • Requirements on architecture.

  • Project Design

    • Discussion on data models, encoding, and querying.
    • Configurations for scalability and reliability in NoSQL databases.
    • Justification for any architectural deviations from the proposed design.

  • Project Implementation

    • Subsections for each component's deployment.
    • Key configuration parameters and considerations.
    • Libraries used, major code snippets.
    • Data models, encoding techniques.
    • Unit tests and integration tests.
    • Subsection on test dataset preparation.

  • Implementation Limitations

    • Discussion on parts not implemented, performance issues, bugs, hardcoded data.

  • Project Demo and Codebase

    • Check Canvas