Improving Search Relevance With Numeric Features in Elasticsearch

Mayya Sharipova • Location: Theater 5Back to Haystack 2019

View the Slides View the Video

Recently Elasticsearch has introduced a number of ways to improve search relevance of your documents based on numeric features. In this talk I will present the newly introduced field types of "rank_feature", "rank_features" ,"dense_field", and "sparse_vector" and discuss in what situations and how they can be used to boost scores of your documents. I will also talk about the inner workings of queries based on these fields, and related performance considerations.

Mayya Sharipova

Mayya Sharipova is a Java engineer at Elastic. She is focusing on supporting current and developing new search features in elasticsearch. She is passionate about how to make search smarter, and cool things that can be be built on top of it.