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Universal Recommender
Open source recommendation engine on Spark + Elasticsearch
About Universal Recommender on Product Hunt
“Open source recommendation engine on Spark + Elasticsearch”
Universal Recommender launched on Product Hunt on August 5th, 2015 and earned 75 upvotes and 2 comments, placing #35 on the daily leaderboard.
Who hunted Universal Recommender?
Universal Recommender was hunted by Thomas R Stone. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Universal Recommender including community comment highlights and product details, visit the product overview.