Summary
In this chapter, we explained scoring and its new default similarity ranking algorithm, BM25, along with explaining the difference between BM25 and TF-IDF, the previous ranking algorithm used in Apache Lucene. In addition to that, we discussed precision and recall, the fundamentals of search relevancy.
After that, we discussed Elasticsearch Query DSL in detail and covered the important queries with their use cases. We also saw the new bool query syntax and how one can use filters within the query context of the bool query. The chapter also covered a detailed discussion about using query rewrites and using search templates along with the Mustache template engine.
In the next chapter, you will learn about query rescoring and how search works in multimatch scenarios, such as cross-field matching and phrase matching. We will also cover various ways to use scripting in Elasticsearch.
