Co-authors: Konstantin Salomatin, Kirill Talanine, Barış Özmen, Gungor Polatkan, Linda Fayad, Arjun Kulothungun, and Deepak Kumar Our vision at LinkedIn is to create economic opportunity for every member of the global workforce. Key to achieving this is making the marketplace between job seekers and hirers more efficient. Active job seekers apply for many jobs,...
Recommender Systems Articles
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Co-authors: Sneha Chaudhari, Mahesh Joshi, and Gungor Polatkan In part 1 of this series, we shared a high-level overview of our course recommendation engine for LinkedIn Learning. First, we provided details on the offline and online components of the system design. Later on, we discussed the three main components of the recommendation engine that are key for...
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Co-authors: Sneha Chaudhari, Mahesh Joshi, and Gungor Polatkan LinkedIn Learning is a platform where LinkedIn members have the opportunity to develop the relevant skills needed to achieve their professional goals. The Learning AI team continually advances the large-scale content recommendation engine for LinkedIn Learning, serving over 690M LinkedIn members and...
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On Aug. 15, 2016, the Machine Learning Algorithm team at LinkedIn gave a hands-on tutorial on how to build recommender systems using...
- Topics:
- machine learning,
- Photon ML,
- Recommender Systems
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LinkedIn makes extensive use of item-based collaborative filtering, which showcases relationships between pairs of items based on the...
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Search plays an important role in online social networks such as LinkedIn, as it provides an essential mechanism for discovering...
- Topics:
- Recommender Systems,
- Paper,
- Search,
- Analytics