Presented to the Bay Area Search Meetup on February 26, 2014
At LinkedIn, we face a number of challenges in delivering high quality search results to 277M+ members. Our results are highly personalized, requiring us to build machine-learned relevance models that combine document, query, and user features. And our emphasis on entities (names, companies, job titles, etc.) affects how we process and understand queries. In this talk, we’ll talk about these challenges in detail, and we’ll describe some of the solutions we are building to address them.
Slides from the presentation