Learning-to-Rank (LTR) is a machine learning technique for improving search results based on user behavior. When faced with complex queries, datasets, or user behavior sometimes search algorithms like BM25 or TF-IDF aren’t enough to render the results we need. Using Solr’s LTR with signals like clickstream data is a powerful way to improve results.
Join us for a webinar to explore Solr’s Learning to Rank functionality. We’ll look at a dataset and how LTR can improve results for that dataset. We’ll also explore how to use Fusion 4 signals as a source for LTR and combining LTR with other techniques for even better results.
This webinar will cover:
- An introduction to Learning-to-Rank
- How to use Learning-to-Rank in Solr
- Tips on providing better results with LTR
- How using Fusion Signals and AI features with LTR will yield even better results
