News Portal Recommendation System Development

We design and deploy artificial intelligence systems: from prototype to production-ready solutions. Our team combines expertise in machine learning, data engineering and MLOps to make AI work not in the lab, but in real business.
8+Years of work900+Completed projects100+In house employees19+Partners
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News Portal Recommendation System Development
Medium
~1-2 weeks
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Implementation of News Portal Recommendation System

News recommendations — balance between personalization and information diversity. Echo-chamber problem is real: if only recommend what user already reads, form information bubble. Plus news quickly becomes outdated: 3-hour-old article more valuable than yesterday's.

Time-Aware Recommendations

Freshness decay rate: for breaking news — aggressive (0.3+), for analytics — gentle (0.05-0.1). Optimal serendipity: 15-25% content outside usual interests. Metrics: CTR (2-5% good for news), session depth (3+ articles), return rate (daily active users %).