111 lines
4.5 KiB
Plaintext
111 lines
4.5 KiB
Plaintext
[[search-suggesters-term]]
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=== Term suggester
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NOTE: In order to understand the format of suggestions, please
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read the <<search-suggesters>> page first.
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The `term` suggester suggests terms based on edit distance. The provided
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suggest text is analyzed before terms are suggested. The suggested terms
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are provided per analyzed suggest text token. The `term` suggester
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doesn't take the query into account that is part of request.
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==== Common suggest options:
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[horizontal]
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`text`::
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The suggest text. The suggest text is a required option that
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needs to be set globally or per suggestion.
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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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suggestion.
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`analyzer`::
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The analyzer to analyse the suggest text with. Defaults
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to the search analyzer of the suggest field.
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`size`::
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The maximum corrections to be returned per suggest text
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token.
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`sort`::
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Defines how suggestions should be sorted per suggest text
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term. Two possible values:
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+
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** `score`: Sort by score first, then document frequency and
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then the term itself.
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** `frequency`: Sort by document frequency first, then similarity
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score and then the term itself.
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+
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`suggest_mode`::
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The suggest mode controls what suggestions are
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included or controls for what suggest text terms, suggestions should be
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suggested. Three possible values can be specified:
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+
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** `missing`: Only provide suggestions for suggest text terms that are
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not in the index. This is the default.
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** `popular`: Only suggest suggestions that occur in more docs then
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the original suggest text term.
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** `always`: Suggest any matching suggestions based on terms in the
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suggest text.
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==== Other term suggest options:
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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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`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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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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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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`min_word_length`::
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The minimum length a suggest text term must have in
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order to be included. Defaults to 4. (Old name "min_word_len" is deprecated)
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`shard_size`::
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Sets the maximum number of suggestions to be retrieved
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from each individual shard. During the reduce phase only the top N
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suggestions are returned based on the `size` option. Defaults to the
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`size` option. Setting this to a value higher than the `size` can be
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useful in order to get a more accurate document frequency for spelling
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corrections at the cost of performance. Due to the fact that terms are
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partitioned amongst shards, the shard level document frequencies of
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spelling corrections may not be precise. Increasing this will make these
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document frequencies more precise.
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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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the shard level. Can improve accuracy at the cost of performance.
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Defaults to 5.
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`min_doc_freq`::
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The minimal threshold in number of documents a
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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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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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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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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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