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sourceDocument: Xanadu ServiceNow AI Platform Administration
sourceDocumentLink: https://servicenow-prod.fluidtopics.net/r/xanadu/platform-administration

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ft:locale :

    - en-US

ft:publication_title :

    - Xanadu ServiceNow AI Platform Administration

ft:clusterId :

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workflow :

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---

# Lemma and Unicode normalization

# Lemma and Unicode normalization {#ariaid-title1}

* Release version: Xanadu
* 
* Updated August 1, 2024
* 
* ![](https://www.servicenow.com/docs/portal-asset/ico-clock) 2 minutes to read

AI Search normalizes inflected words and Unicode glyphs during indexing and at search query time. Normalization improves search recall and enables users to find content with variant forms of their search query
terms.

Normalization features are automatically enabled and aren't configurable.

## Lemma normalization {#lemma-unicode-normalization-ais__section_igg_pc5_fnb}

Many languages include inflected forms of terms, such as plural nouns or verb tenses. AI Search normalizes inflected terms found in indexed content and search queries. Normalization enables matching based on a root form, such as the singular for a plural noun or the base form for a conjugated
verb. This root form is called a lemma, and this process is referred to as lemma normalization.

For example, when a source record includes the conjugated verb <kbd class="ph userinput">selling</kbd>, AI Search expands the indexed term to include the lemma form sell in addition to selling. When a user searches for the past-tense conjugated form
<kbd class="ph userinput">sold</kbd>, AI Search expands the search query term to include the lemma form sell as well as sold. Because the indexed term and the search query term include
matching forms, the user's search returns the <kbd class="ph userinput">selling</kbd> record as a result.

AI Search supports language-specific lemma normalization for Brazilian Portuguese, Dutch, English, Finnish, French, French - Canada, German, Italian, Japanese, Korean, Norwegian (Bokmål), Polish, Portuguese, Simplified Chinese, Spanish, Swedish, and Traditional Chinese.

## Decompounding {#lemma-unicode-normalization-ais__section_cjq_4rg_4rb}

In addition to normalizing lemmas for German, Korean, Norwegian (Bokmål), and Swedish, AI Search indexes compound words and their individual component words. For example, when indexing a German record that contains the compound word <kbd class="ph userinput">Humanressourcen</kbd>, AI Search indexes the component terms Human and ressourcen in addition to the compound term.

## Unicode normalization {#lemma-unicode-normalization-ais__section_udc_mcw_3nb}

AI Search performs Unicode normalization on indexed terms and search query terms. This normalization makes alphabetical Unicode glyphs searchable using their nearest equivalent characters.

For example, when indexing a record containing the term <kbd class="ph userinput">resumé</kbd>, AI Search expands the term to also include the non-accented form resume. This record appears as a search result when users search for either resume or
resumé.

Unicode normalization includes NFKD (compatibility decomposition) and NFKC (compatibility composition) stages. For more information on these normalization forms, see the Unicode Standard Annex #15, <https://www.unicode.org/reports/tr15/>.

## Interaction with other search features {#lemma-unicode-normalization-ais__section_p3f_wsy_2nb}

The following table describes interactions between normalization and other search features.  
{#lemma-unicode-normalization-ais__table_vdr_yd5_fnb__entry__2}

| Feature | Interaction with lemma and Unicode normalization |
|-|-|
| [Genius Results](https://servicenow-prod.fluidtopics.net/tifPTb4QLvFRp1Vwd2sMcQ "Optionally display the best answers for a search query as actionable Genius Result cards included with search results.") | Search query terms added by lemma or Unicode normalization can't trigger Genius Result configurations with Term trigger conditions. |
| [Result improvement rules](https://servicenow-prod.fluidtopics.net/J~mLT_HXtldLRqaNKcQgSw "Define rules with configurable trigger conditions to boost, block, or promote search results for specific searches. You can also boost search results for documents matching elements of the user context, such as a user's country, OS, or device type.") | A search query term added by lemma or Unicode normalization can trigger a result improvement rule if it matches the rule's Query trigger. |
| [Stop words](https://servicenow-prod.fluidtopics.net/Cim4Rf8qhGT64T_dt2XUZA "Stop words remove search query terms that don't produce meaningful results. Improve search precision and relevancy by configuring stop word dictionaries and defining stop words.") | If a search query term is defined as a stop word, AI Search removes that term without normalizing it. |
| [Synonyms](https://servicenow-prod.fluidtopics.net/cjrGZ8bePEfjKrApMpyYnQ "Synonyms expand search queries to include additional terms with equivalent meaning or usage. Improve search recall by configuring synonym dictionaries and defining synonyms.") | If a search query term is defined as a synonym, AI Search doesn't normalize it. |
| [Typo handling](https://servicenow-prod.fluidtopics.net/pmfC8lQxxBx7TjVN98~VRA "AI Search replaces misspelled search query terms with auto-correction terms derived from indexed content. Configure typo handling dictionary settings to control derivation of auto-correction terms.") | AI Search performs lemma and Unicode normalization on auto-corrected search query terms. |
[ ]

{#lemma-unicode-normalization-ais__table_vdr_yd5_fnb}