The document discusses improving recommendations by tracking user browsing behavior and using collaborative filtering. It currently uses content-based recommendations from Solr but this does not consider user relevance. The new approach would generate events with user_id, slideshow_id, and platform for analyzed user behavior data. Apache Mahout would then use this behavioral data with collaborative filtering to provide recommendations with a higher priority for each user, helping to improve engagement. It demonstrates setting up Hadoop and Mahout to analyze a week of user log data and generate recommendations.