Learning to Rank with Apache Solr and Fusion

When faced with complex queries, datasets, or user behavior, basic search algorithms aren’t always enough to render the results we need. Learning to Rank (LTR) is a machine learning technique in Apache Solr for improving search results based on user behavior.

This webinar explores Apache Solr’s Learning to Rank functionality and how it can be used to yield better search results. We’ll also learn how Lucidworks Fusion leverages signals as a source for LTR to yield even better outcomes.

In this webinar, you’ll learn:

• Tips on how to leverage Learning to Rank in Apache Solr and Lucidworks Fusion
• Why using Learning to Rank is a powerful machine learning technique that provides the most relevant search results
• An introduction to using Fusion AI features such as signals, signal boosting, ground truth jobs, and pipelines

Additional Resources:

• Article on the ABCs of Learning to Rank
• View the slides of the presentation
• Check out the Learning to Rank ebook
• Get the tutorial code from GitHub

Featuring:

Andy Liu

Senior Data Scientist, Lucidworks

Trey Grainger

Chief Algorithms Officer, Lucidworks