Co-authors: Benjamin McCann and Nadeem Anjum Last June, we introduced Recommended Matches: candidate recommendations for your open job posting that get more targeted over time based on your feedback. We're now rolling out this feature globally alongside an updated version of the algorithm powering it. This new algorithm, which is used throughout the Jobs...
relevance Articles
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Co-authors: Xi Chen, Yiqun Liu, Liang Zhang, and Krishnaram Kenthapadi Online professional social networks and job platforms, such as LinkedIn, play a key role in ensuring an efficient labor marketplace by connecting talent (job seekers) with opportunities (jobs). Studies show that salary is an important factor when looking for new opportunities, but salary...
- Topics:
- relevance,
- economic graph,
- machine learning,
- research,
- Data,
- Product Design
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Co-authors: Bonnie Barrilleaux and Dylan Wang Our 567M members use the LinkedIn feed to talk to each other a lot: more than a million posts, videos, and articles flow through the LinkedIn feed each day. This is the story of how we discovered some growing pains for both creators and viewers in the feed; how we solved the problems with a smarter feed relevance...
- Topics:
- Feed Personalization ,
- A/B Testing,
- data science,
- experimentation,
- Data,
- relevance,
- T-REX
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Co-authors: Sahin Cem Geyik and Krishnaram Kenthapadi Introduction: Building products that create opportunity Motivated by LinkedIn’s...
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Editor’s note: The use of AI in LinkedIn products has been the subject of multiple press articles and research papers (some...
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The Microsoft acquisition of LinkedIn brought many opportunities for combining technologies to do something new and useful. One such...
- Topics:
- relevance,
- machine learning,
- Product Design