In the previous chapter, we learned what scoring is and how Elasticsearch calculates it. When an application grows, the need for improving the quality of search also increases. We call it the search experience. We need to gain knowledge about what is more important to the user and see how users use the search functionality. This leads to various conclusions; for example, we see that some parts of the documents are more important than the others or that particular queries emphasize one field at the cost of others. This is where boosting can be used.
Boost is an additional value used in the process of scoring. We already know it can be applied to the following:
query: This is a way to inform the search engine that the given query is a part of the complex query and is more significant than the others.field: Several document fields are important for the user. For example, searching e-mails by Bill should probably list those from Bill first, followed...