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Product Ecosystem Optimization at LinkedIn

Published:25 July 2019Publication History

ABSTRACT

Artificial Intelligence (AI) is behind practically every product experience at LinkedIn. From ranking the member's feed to recommending new jobs, AI is used to fulfill our mission to connect the world's professionals to make them more productive and successful. While product functionality can be decomposed into separate components, they are deeply interconnected; thus, creating interesting questions and challenging AI problems that need to be solved in a sound and practical manner. In this talk, I will provide an overview of lessons learned and approaches we have developed to address these problems, including scaling to large problem sizes, handling multiple conflicting objective functions, efficient model tuning, and our progress toward using AI to optimize the LinkedIn product ecosystem more holistically.

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  • Published in

    cover image ACM Conferences
    KDD '19: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
    July 2019
    3305 pages
    ISBN:9781450362016
    DOI:10.1145/3292500

    Copyright © 2019 Owner/Author

    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    • Published: 25 July 2019

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    • invited-talk

    Acceptance Rates

    KDD '19 Paper Acceptance Rate110of1,200submissions,9%Overall Acceptance Rate1,133of8,635submissions,13%

    Upcoming Conference

    KDD '24
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