Elasticsearch Learning to Rank - Search as an Machine Learning Problem

Details

For our first meetup, Doug Turnbull from OpenSource Connections, author of Relevant Search, will be speaking about Elasticsearch Learning to Rank! LexisNexis will be our gracious hosts and sponsors!

/* Tonight's Presentation Summary: */
Search relevance is how user queries are answered through search. It's the process of changing the ranking of search results for a user query to return what users want. A search for 'iPhone XS' should rank documents highly when the product name matches. But a different query, 'smartphone with two cameras' would require a completely different strategy for ranking candidate results. What gives teams a headache is that all the diverse use cases for search must be handled by a single ranking algorithm.

This is where Learning to Rank comes in. We will discuss how search can be treated as a machine learning problem. 'Learning to Rank' takes the step to returning optimized results to users based on patterns in usage behavior. We will talk through where Learning to Rank has shined, as well as the limitations of a machine learning-based solution to improve search relevance.

/* Evening Schedule: */

• 6:00pm - Food will be served!
• 6:45pm - We will begin the evening presentation.
• 8:00pm - Time to close up and leave.

/* Location Details: */

The meeting will take place at the LexisNexis offices on NC State's Centennial Campus. In the building, you'll go to Centennial Hall to the left when you enter the office at the front