Co-authors: Ian Ackerman and Saurabh Kataria Editor’s Note: Multi-objective optimization (MOO) is used for many products at LinkedIn (such as the homepage feed) to help balance different behaviors in our ecosystem. There are two parts to how we work with multiple objectives: the first is about training high-fidelity models to predict member behavior (e.g.,...
Feed Personalization Articles
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Co-authors: Chiachi Lo, Bohong Zhao, and Elina Lin When we launched a major redesign of LinkedIn’s mobile application and desktop web experiences a few years back, we focused the My Network tab to help professionals connect with each other on LinkedIn through our People You May Know feature. Over time, we realized there was much more we could do to help our 706M...
- Topics:
- relevance,
- artificial intelligence,
- Feed Personalization ,
- Data
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Co-authors: Siddharth Dangi, Johnson Jia, Manas Somaiya, and Ying Xuan The LinkedIn feed is the cornerstone of the member experience. It’s where our members post ideas, career news, questions, and jobs in an array of formats, including short text, long-form articles, images, and videos. The Feed AI Team’s mission is to help LinkedIn’s members discover the most...
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Serving the most relevant information for LinkedIn members in the homepage feed requires a massive effort—hundreds of features are...
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As the year draws to a close, we’re taking a look back at ten of our most popular 2019 articles on the LinkedIn Engineering Blog....
- Topics:
- artificial intelligence,
- Pinot,
- Feed Personalization ,
- Security,
- Kafka,
- SRE
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The LinkedIn feed relies on a ranked list of the most relevant content for a member. More than 80% of the feed is organic content...
- Topics:
- FollowFeed,
- Feed Personalization ,
- Kafka,
- Data