Building Recommendation Engine with Graph Database

Graph Databases analyze and aggregate data.Recommendation Engines use Collaborative Filtering.

Collaborative Filtering follows these steps –

  • Generate Signals
  • Build Item Recommendation
  • Build a Personal Recommendation
  • Store Results in Database
  • Recommendation API integration
  • Perform Recommendation on User Application
  • Recommendation to Users
  • Users Action or Item Data stored in Database

Recommendation System using Graph Database executes following steps –

  • Import Data to insert source data within the tables
  • Construction of Graph
  • Perform Graph Query
  • Optimize Performance
  • Graph Visualization

Real-Time Recommendation System Applications using Graph Database –

  • Movie Recommendation System
  • E-Commerce Sites
  • Social Media Applications
  • Fraud Detection
  • Search Engines
  • Access Management