Co-authors: Vivek Nelamangala and Val Markovic Editor’s note: In Part 1 of this series, we talked about how we built the Activity Graph and how we use it to deliver features to Activity searcher machines. In this post, we’ll talk about how we store this data for efficient storage and retrieval. Quick background on FollowFeed FollowFeed is the main Activity...
Feed Personalization Articles
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- Topics:
- relevance,
- Feed Personalization
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Co-authors: Val Markovic and Vivek Nelamangala Serving a feed of relevant, personalized content to 500 million members is a massive undertaking. Accordingly, our feed infrastructure is constantly evolving to take advantage of new relevance models, new features, and more efficient ways of scaling our infrastructure. In this post, we describe the Activity Graph,...
- Topics:
- relevance,
- Feed Personalization
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Co-authors: Rushi Bhatt and Bari Saltman LinkedIn’s home feed is the starting point of a member’s journey on LinkedIn. Millions of members see the feed as their first impression. The feed is also instrumental to delivering on LinkedIn’s core value propositions: it allows members to stay connected with their network by following network activities, to build their...
- Topics:
- relevance,
- machine learning,
- Feed Personalization
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Coauthors: Alexandre Patry, Diego Buthay One of the responsibilities of the LinkedIn Feed team is to deliver news and information in...
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Coauthors: Swapnil Ghike, Shubham Gupta The feed is the default landing experience for LinkedIn’s members. It helps them discover the...
- Topics:
- FollowFeed,
- Feed Personalization ,
- Feed Data Platform,
- SenseiDB
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This is a follow up post to Making Your Feed More Relevantthat provided introductory background on the feed system at LinkedIn. In...
- Topics:
- Feed Personalization