Databricks Neo4j Content Recommender

@arturg6

Hello, "DATAGRICKS NEO4J CONTENT RECOMMENDER" — you need to suggest articles, videos or music based on user behavior. I’ll pull user logs from Databricks Delta Lake, turn them into graph edges, and run Neo4j Graph Data Science node2vec embeddings to generate fast recommendations. This keeps latency under 200 ms even with millions of interactions. For cold‑start items I’ll fall back to content‑based similarity using the metadata you provide, so new videos get ranked immediately. Could you share the schema of your current Neo4j nodes and the format of the behavior logs you plan to feed in? Looking forward to working with you. Artur Giżycki

@PINESCRIPTERR

Hi, I can help build a content recommendation engine on Databricks with Neo4j as the graph layer, using user behavior and content metadata to recommend articles, videos, music, or other entertainment assets. I’d design the system around a hybrid recommendation approach: collaborative signals from user behavior, content-based features from metadata, and graph-based relationships in Neo4j such as users, content, genres, tags, creators, sessions, likes, skips, watches, and similarity edges. Databricks would handle ingestion, cleaning, feature engineering, model training, batch scoring, and evaluation, while Neo4j would support relationship-aware recommendations and explainable paths like “recommended because users with similar interests watched this.” The workflow would include data pipelines, graph schema design, feature tables, candidate generation, ranking logic, evaluation metrics, and an API or export layer for serving recommendations. I’d keep the architecture modular so you can later add real-time signals, A/B testing, or personalized ranking models. Question 1: Is your user behavior data already stored in Databricks, or does ingestion need to be built? Question 2: Do you need batch recommendations only, or near real-time recommendations as well? Regards, Houssame

@ZohaibRoy

⭐⭐⭐⭐⭐ Create a Smart Content Recommender System with Databricks & Neo4j ❇️ Hi My Friend, I hope you're doing well. I've reviewed your project requirements and noticed you're looking for a content recommender system on Databricks using Neo4j. You have no need to look any further; Zohaib is here to help you! My team has successfully completed 50+ similar projects for content recommendation systems. I will utilize user behavior data and content metadata to build an effective solution, ensuring you get the best results within your budget. ➡️ Why Me? I can easily create your content recommender system as I have 5 years of experience in building efficient systems using Databricks and Neo4j. My expertise includes analyzing user behavior data, content metadata, and designing algorithms for recommendations. Besides, I have a strong grip on data integration and analysis, ensuring a seamless approach to your project. ➡️ Let's have a quick chat to discuss your project in detail and let me show you samples of my previous work. Looking forward to discussing this with you in our chat. ➡️ Skills & Experience: ✅ Databricks ✅ Neo4j ✅ Recommender Systems ✅ User Behavior Analysis ✅ Content Metadata Handling ✅ Data Integration ✅ Data Analysis ✅ Algorithm Design ✅ Python Programming ✅ SQL ✅ Machine Learning ✅ Data Visualization Waiting for your response! Best Regards, Zohaib