Improving information retrieval in the Elastic Stack
This series explores steps to improve search relevance, benchmarking passage retrieval, ELSER, and hybrid retrieval.
Improving information retrieval in the Elastic Stack: Steps to improve search relevance
In this first blog post, we will list and explain the differences between the primary building blocks available in the Elastic Stack to do information retrieval.
Improving information retrieval in the Elastic Stack: Benchmarking passage retrieval
In this blog post, we'll examine benchmark solutions to compare retrieval methods. We use a collection of data sets to benchmark BM25 against two dense models and illustrate the potential gain using fine-tuning strategies with one of those models.
Improving information retrieval in the Elastic Stack: Introducing Elastic Learned Sparse Encoder, our new retrieval model
Learn about the Elastic Learned Sparse Encoder (ELSER), its retrieval performance, architecture, and training process.
Improving information retrieval in the Elastic Stack: Hybrid retrieval
In this blog we introduce hybrid retrieval and explore two concrete implementations in Elasticsearch. We explore improving Elastic Learned Sparse Encoder’s performance by combining it with BM25 using Reciprocal Rank Fusion and Weighted Sum of Scores.