The language settings affect both your data (indexing language) as well as the search queries (query languages), for example, splitting the query into words (tokenization), or the treatment of plurals.
To change the settings appropriate for the language you want to support:
foot
and feet
should return the same results.
You can add custom plurals and other declensions to a dictionary.
Stop words are common words that don’t add much information, such as articles, prepositions, or conjunctions. They’re filtered out from every search. To configure stop words:
Algolia uses stop word dictionaries for every query language. You can add more stop words to the dictionary.
When users search with a compound word, Algolia segments the compound word into its constituents and searches for the individual words instead. This returns more results for languages with many compound words. Algolia supports segmenting compound words in Dutch, German, Finnish, Danish, Swedish, and Norwegian Bokmål. Word segmentation is turned on by default if you use one of these languages as the query language,
If you want to index compound words in one or more of your searchable attributes as separate words:
Compound words that are in a decompounded attribute are indexed separately. The same compound word in another attribute is indexed as one word.
Algolia uses dictionaries for every query language to determine word segmentation. You can add compound words to the dictionary and decide if you want to segment them or keep them as one word when searching. In some scenarios, it’s better to keep compound words, for example, when searching for brand names.
Synonyms let your users use different words to search for the same products. For example, some users look for “pants”, while others might search for “trousers”—both meaning the same. If you add “pants” and “trousers” as synonyms, both searches return the same results.
Algolia’s Dynamic Synonym Suggestions suggest synonyms based on your users’ searches. You can also add synonyms manually, based on your internal business data. For example, if you’re working in a field with a lot of industry-specific terminology, you can use this information to ensure your users always find what they’re looking for.