Recommendation System
iNews Recommendation Engine
Personalized news recommendations using behavior signals.
Backend Developer | 2022 - 2024
Portfolio overview
Engineered a recommendation backend that combined geolocation and behavior patterns to personalize article feeds for a large media audience.
Built recommendation services that fused user behavior and geolocation context to better rank content for each audience segment.
The service architecture prioritized response time and scalability for high-read traffic patterns.
Key impact
- Increased recommendation relevance with Elasticsearch ranking logic.
- Cut response latency using Redis-backed hot data caching.
- Improved content discovery for high-traffic sections.
Technologies used
- Go
- MongoDB
- Elasticsearch
- Redis
- Microservices