Trey Grainger

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Chief Algorithms Officer
Lucidworks

Trey is the Chief Algorithms Officer at Lucidworks, where he drives vision and practical application of intelligent data science algorithms to power relevant search experiences for hundreds of the worlds biggest and brightest companies. He is also the co-author of Solr in Action, plus more than a dozen additional books, journal articles, and research publications covering industry-leading approaches to semantic search, recommendation systems, and intelligent information retrieval systems. Trey received his Masters in Management of Technology from Georgia Tech, studied Computer Science, Business, and Philosophy at Furman University, and studied Information Retrieval and Web Search at Stanford University.

Trey Grainger is speaking at the following session/s

Natural Language Search with Knowledge Graphs

Wednesday | 3:20PM - 4:00PM | Lincoln East

To optimally interpret most natural language queries, its important to understand a highly-nuanced, contextual interpretation of the domain-specific phrases, entities, commands, and relationships represented or implied within the search and within your domain.

In this talk, we'll walk through such a search system powered by Solr's Text Tagger and Semantic Knowledge graph. We'll have fun with some of the more search-centric use cases of knowledge graphs, such as entity extraction, query expansion, disambiguation, and pattern identification within our queries: for example, transforming the query "best bbq near activate" into:

{!func}mul(min(popularity,1),100) bbq^0.91032 ribs^0.65674 brisket^0.63386 doc_type:"restaurant" {!geofilt d=50 sfield="coordinates_pt" pt="38.916120,-77.045220"}

We'll see a live demo with real world data demonstrating how you can build and apply your own knowledge graphs to power much more relevant query understanding like this within your search engine.

Attendee Takeaway
The audience will learn about Semantic Knowledge Graphs, how to build them, how to use them, how to combine them with entity extraction through Solr's Text Tagger, and how to build a search application that adequately interprets the nuanced meanings associated with natural language queries.

Intended Audience
This talk is for developers familiar with Solr and interested in search relevance. Basic knowledge of Solr's query syntax is assumed.

Closing Keynote: The Next Generation of AI-powered Search

Thursday | 4:15PM - 4:45PM | International Ballroom

What does it really mean to deliver an "AI-powered Search" solution? In this talk, we’ll bring clarity to this topic, showing you how to marry the art of the possible with the real-world challenges involved in understanding your content, your users, and your domain. We'll dive into emerging trends in AI-powered Search, as well as many of the stumbling blocks found in even the most advanced AI and Search applications, showing how to proactively plan for and avoid them. We'll walk through the various uses of reflected intelligence and feedback loops for continuous learning from user behavioral signals and content updates, also covering the increasing importance of virtual assistants and personalized search use cases found within the intersection of traditional search and recommendation engines. Our goal will be to provide a baseline of mainstream AI-powered Search capabilities available today, and to paint a picture of what we can all expect just on the horizon.

Level:
All Levels