Quantitative full-text search tuning

During the design of our Elasticsearch setup and its search queries, we often make assumptions on how the customer will use our search engine.

In this lightning talk I will show you how to leverage real-world user data to tune Elasticsearch full-text search based on a quantitative analysis. I will cover the following topics:

• What are the key metrics used for information retrieval in full-text searches?
• How can we leverage real-world user data to improve our full-text search?
• How can we run a quantitative analysis on our full-text search engine?
• How can we make sure that changing our Elasticsearch query does not negatively affect the overall quality of the full-text search engine?
• How can we sustainably improve the quality of our full-text search engine?

I will dive into defining our key metrics, collecting real-world user data, running a quantitative analysis on your full-text search, and finally iterating to improve key metrics.

Lightning talk Advanced Enterprise search Stack