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Edits to text & formatting in Term Suggester doc (#38963)
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docs/reference/search/suggesters/term-suggest.asciidoc

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@@ -18,7 +18,7 @@ doesn't take the query into account that is part of request.
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`field`::
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The field to fetch the candidate suggestions from. This is
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an required option that either needs to be set globally or per
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a required option that either needs to be set globally or per
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suggestion.
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`analyzer`::
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[horizontal]
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`lowercase_terms`::
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Lower cases the suggest text terms after text analysis.
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Lowercases the suggest text terms after text analysis.
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`max_edits`::
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The maximum edit distance candidate suggestions can
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have in order to be considered as a suggestion. Can only be a value
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between 1 and 2. Any other value result in an bad request error being
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between 1 and 2. Any other value results in a bad request error being
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thrown. Defaults to 2.
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`prefix_length`::
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The number of minimal prefix characters that must
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match in order be a candidate suggestions. Defaults to 1. Increasing
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match in order be a candidate for suggestions. Defaults to 1. Increasing
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this number improves spellcheck performance. Usually misspellings don't
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occur in the beginning of terms. (Old name "prefix_len" is deprecated)
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`max_inspections`::
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A factor that is used to multiply with the
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`shards_size` in order to inspect more candidate spell corrections on
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`shards_size` in order to inspect more candidate spelling corrections on
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the shard level. Can improve accuracy at the cost of performance.
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Defaults to 5.
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suggestion should appear in. This can be specified as an absolute number
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or as a relative percentage of number of documents. This can improve
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quality by only suggesting high frequency terms. Defaults to 0f and is
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not enabled. If a value higher than 1 is specified then the number
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not enabled. If a value higher than 1 is specified, then the number
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cannot be fractional. The shard level document frequencies are used for
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this option.
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`max_term_freq`::
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The maximum threshold in number of documents a
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The maximum threshold in number of documents in which a
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suggest text token can exist in order to be included. Can be a relative
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percentage number (e.g 0.4) or an absolute number to represent document
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frequencies. If an value higher than 1 is specified then fractional can
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percentage number (e.g., 0.4) or an absolute number to represent document
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frequencies. If a value higher than 1 is specified, then fractional can
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not be specified. Defaults to 0.01f. This can be used to exclude high
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frequency terms from being spellchecked. High frequency terms are
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usually spelled correctly on top of this also improves the spellcheck
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performance. The shard level document frequencies are used for this
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option.
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frequency terms -- which are usually spelled correctly -- from being spellchecked.
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This also improves the spellcheck performance. The shard level document frequencies
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are used for this option.
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`string_distance`::
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Which string distance implementation to use for comparing how similar
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suggested terms are. Five possible values can be specified:
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`internal` - The default based on damerau_levenshtein but highly optimized
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** `internal`: The default based on damerau_levenshtein but highly optimized
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for comparing string distance for terms inside the index.
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`damerau_levenshtein` - String distance algorithm based on
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** `damerau_levenshtein`: String distance algorithm based on
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Damerau-Levenshtein algorithm.
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`levenshtein` - String distance algorithm based on Levenshtein edit distance
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** `levenshtein`: String distance algorithm based on Levenshtein edit distance
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algorithm.
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`jaro_winkler` - String distance algorithm based on Jaro-Winkler algorithm.
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`ngram` - String distance algorithm based on character n-grams.
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** `jaro_winkler`: String distance algorithm based on Jaro-Winkler algorithm.
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** `ngram`: String distance algorithm based on character n-grams.

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