Chief Technical Officer
Author of Relevant Search. CTO of OpenSource Connections. As a consultant, Doug's mission is to help teams understand the intersection of AI-driven search technology, organizational challenges, and user needs. Towards this mission, Doug enjoys training teams on Solr Relevance and Learning to Rank, helping teams organize to be "relevance-centered enterprise", and guiding teams to a cohesive relevance strategy.
Doug loves learning, writing about search on OpenSource Connection's blog, and working on tools that enable Solr relevancy delivery, including Quepid, Splainer and Elyzer.
Doug Turnbull is speaking at the following session/s
Conversion Models: A Systematic Method of Building Learning to Rank Training Data
When using user signals to improve relevance, what should you use? Clicks are more frequent, but really only correspond to a search result looking attractive. A conversion is a powerful signal of true relevance but occurs less frequently. Can we combine shallow "this looks interesting" click events along with strong, but rare conversion signals in a robust fashion to generate learning to rank training data? In this talk, we introduce click models, an industry-proven way of measuring search result attractiveness from clicks, and propose a systematic way of incorporating conversion data into click models. Whether your industry is conversion heavy (like e-commerce), or lacking in any clear conversion signal (like publishing) you'll take away from this talk a system for turning any search analytics into robust judgments and training data. Because, after all, there is no AI-based Search without good training data!
- Making sense of how to use analytics to measure search quality
- Using analytics to train learning to rank and other machine learning models
- How and why bad analytics dooms machine learning projects
- A systematic approach to using analytics in search no matter the nature of your application
- Data scientists, relevance engineers, data engineers , ML engineers, product managers who need to use analytics to measure search quality
- Some basic math is required, but this talk is tailored towards anyone, indenting to give you an appreciation on how to use analytics in search