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Wednesday, October 17 • 11:15am - 11:55am
Learning to Rank: From Theory to Production

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Learning to Rank is awesome. Even more awesome is the fact that Apache Solr/Lucene is the first open source search engine that can do it out of the box. But all that is for nought if you don't hunt down the necessary features, make it interoperate with all the other functionality, and do this fast enough on a production system for such ranking to be feasible.

This talk, by the engineers at Bloomberg who built this functionality into Solr in the first place, is a war story of how the company's real-time, low-latency news search engine was tamed to learn how to rank. Join us on a journey that will teach you how to take your LtR system to your clients, and more importantly, the many ways not to do it. There will be drama, excitement, and despair (and even Gandalf, if you pay attention)! Now grab that popcorn...

avatar for Diego Ceccarelli

Diego Ceccarelli

Software Engineer, Bloomberg
Diego is a Software Engineer at Bloomberg LP, working in the News Search R&D team. His work focuses on improving search relevance for financial news. Before joining Bloomberg, Diego was a researcher in Information Retrieval at the National Council of Research in Italy, whilst completing... Read More →
avatar for Malvina Josephidou

Malvina Josephidou

Software Engineer, Bloomberg
I am a software engineer in the News R&D team at Bloomberg. My work focuses on using machine learning to improve search relevance and discoverability on the news search engine. Previous to this I completed my PhD at the University of Cambridge in statistics and computational biology... Read More →

Wednesday October 17, 2018 11:15am - 11:55am EDT
Drummond East