Real-Time Recommendations
Blog post from Neo4j
The blog features a collection of articles and case studies focused on the application of graph databases and analytics in various domains such as real-time recommendations, job search experiences, and digital twins. It highlights examples of using graph analytics in platforms like Snowflake and Neo4j to unlock high-conversion recommendations, delves into the intuition behind the Jaccard coefficient for recommendation systems, and explores practical implementations like building a recommendation engine. Additionally, it presents real-world case studies on how organizations such as Apna and governmental bodies use graph databases to enhance job search experiences and improve traffic operations, respectively. Other articles cover the development of data-driven tools for career development and engagement, as well as initiatives like Developers.Zed, designed to connect developers in Zambia using graph analytics.