119 lines
2.9 KiB
Plaintext
119 lines
2.9 KiB
Plaintext
[[analysis-fingerprint-analyzer]]
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=== Fingerprint Analyzer
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The `fingerprint` analyzer implements a
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https://github.com/OpenRefine/OpenRefine/wiki/Clustering-In-Depth#fingerprint[fingerprinting algorithm]
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which is used by the OpenRefine project to assist in clustering.
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Input text is lowercased, normalized to remove extended characters, sorted,
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deduplicated and concatenated into a single token. If a stopword list is
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configured, stop words will also be removed.
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[float]
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=== Definition
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It consists of:
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Tokenizer::
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* <<analysis-standard-tokenizer,Standard Tokenizer>>
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Token Filters (in order)::
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1. <<analysis-lowercase-tokenfilter,Lower Case Token Filter>>
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2. <<analysis-asciifolding-tokenfilter>>
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3. <<analysis-stop-tokenfilter,Stop Token Filter>> (disabled by default)
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4. <<analysis-fingerprint-tokenfilter>>
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[float]
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=== Example output
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[source,js]
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---------------------------
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POST _analyze
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{
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"analyzer": "fingerprint",
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"text": "Yes yes, Gödel said this sentence is consistent and."
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}
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---------------------------
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// CONSOLE
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The above sentence would produce the following single term:
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[source,text]
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---------------------------
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[ and consistent godel is said sentence this yes ]
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---------------------------
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[float]
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=== Configuration
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The `fingerprint` analyzer accepts the following parameters:
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[horizontal]
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`separator`::
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The character to use to concate the terms. Defaults to a space.
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`max_output_size`::
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The maximum token size to emit. Defaults to `255`. Tokens larger than
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this size will be discarded.
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`preserve_original`::
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If `true`, emits two tokens: one with ASCII-folding of terms that contain
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extended characters (if any) and one with the original characters.
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Defaults to `false`.
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`stopwords`::
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A pre-defined stop words list like `_english_` or an array containing a
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list of stop words. Defaults to `_none_`.
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`stopwords_path`::
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The path to a file containing stop words.
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See the <<analysis-stop-tokenfilter,Stop Token Filter>> for more information
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about stop word configuration.
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[float]
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=== Example configuration
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In this example, we configure the `fingerprint` analyzer to use the
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pre-defined list of English stop words, and to emit a second token in
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the presence of non-ASCII characters:
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[source,js]
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----------------------------
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PUT my_index
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{
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"settings": {
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"analysis": {
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"analyzer": {
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"my_fingerprint_analyzer": {
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"type": "fingerprint",
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"stopwords": "_english_",
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"preserve_original": true
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}
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}
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}
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}
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}
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GET _cluster/health?wait_for_status=yellow
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POST my_index/_analyze
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{
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"analyzer": "my_fingerprint_analyzer",
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"text": "Yes yes, Gödel said this sentence is consistent and."
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}
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----------------------------
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// CONSOLE
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The above example produces the following two terms:
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[source,text]
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---------------------------
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[ consistent godel said sentence yes, consistent gödel said sentence yes ]
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---------------------------
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