Reciprocal Rank Fusion (RRF) or How to Stop Worrying about Boosting

Reciprocal rank fusion (RRF) combines multiple result sets with different relevance indicators — like lexical and dense or sparse vector search — into a single result set. One of the great attributes of RRF is that it requires no tuning, and the different relevance indicators do not have to be related to each other to achieve high-quality results. If you have been using boosting to combine different types of searches, this is the talk for you. We’ll dive into the algorithm, how to use it, and how it might surprise you when coming from BM25 search.

Philipp Krenn

Elastic

Philipp lives to demo interesting technology. Having worked as a web, infrastructure, and database engineer for over ten years, Philipp is now a developer advocate and team lead at Elastic — the company behind the Elastic Stack consisting of Elasticsearch, Kibana, Beats, and Logstash.