While stemming helps to broaden the scope of search by simplifying inflected words to their root form, synonyms broaden the scope by relating concepts and ideas. Perhaps no documents match a query for “English queen,” but documents that contain “British monarch” would probably be considered a good match.

A user might search for “the US” and expect to find documents that contain United States, USA, U.S.A., America, or the States. However, they wouldn’t expect to see results about the states of matter or state machines.

This example provides a valuable lesson. It demonstrates how simple it is for a human to distinguish between separate concepts, and how tricky it can be for mere machines. The natural tendency is to try to provide synonyms for every word in the language, to ensure that any document is findable with even the most remotely related terms.

This is a mistake. In the same way that we prefer light or minimal stemming to aggressive stemming, synonyms should be used only where necessary. Users understand why their results are limited to the words in their search query. They are less understanding when their results seems almost random.

Synonyms can be used to conflate words that have pretty much the same meaning, such as jump, leap, and hop, or pamphlet, leaflet, and brochure. Alternatively, they can be used to make a word more generic. For instance, bird could be used as a more general synonym for owl or pigeon, and adult could be used for man or woman.

Synonyms appear to be a simple concept but they are quite tricky to get right. In this chapter, we explain the mechanics of using synonyms and discuss the limitations and gotchas.


Synonyms are used to broaden the scope of what is considered a matching document. Just as with stemming or partial matching, synonym fields should not be used alone but should be combined with a query on a main field that contains the original text in unadulterated form. See Most Fields for an explanation of how to maintain relevance when using synonyms.