@ezs/teeft v2.3.2
teeft
Présentation
Ce plugin propose une série d'instructions pour extraire des mots-clés d'un texte français ou anglais en utilisant l'algorithme Teeft.
C'est le paquet officiel qui fait suite à l'expérimentation ezs-teeftfr.
Bibliographie
Cuxac P., Kieffer N., Lamirel J.C. : SKEEFT: indexing method taking into account the structure of the document. 20th Collnet meeting, 5-8 Nov 2019, Dalian, China.
Installation
npm install @ezs/core
npm install @ezs/teeftFlux
Le principe est de décomposer le flux en une série d'instructions ayant chacune ses propres paramètres (voir usage).
Voici la séquence typique d'instructions qui permet de lire les fichiers .txt
d'un répertoire et de les envoyer aux tokenizers de phrase, puis de mots;
ensuite on procède à un étiquetage grammatical, puis on extrait les termes, et
on les filtre (par fonction grammaticale), on enlève les nombres, on supprime
les mots vides, on calcule les fréquences des tokens, puis leur spécificité,
enfin, on les filtre suivant leur fréquence.
[ "/path/to/a/directory/of/documents" ] ->
[TeeftListFiles]
pattern = *.txt
--> [ "/path1", "path2", ... ] -->
[TeeftGetFilesContent]
--> [ { path, content }, ... ] -->
[TeeftSentenceTokenize]
--> [ { path, sentences: [ "sentence", ... ] }, ... ] -->
[TeeftTokenize]
--> [ { path, sentences: [ ["token", ... ], ...] }, ... ] -->
[TeeftNaturalTag]
--> [ { path, sentences: [ [
{
token: "token",
tag: [ "tag", ...]
}, ...
], ... ] }, ... ]
[TeeftExtractTerms]
nounTag = NOM
adjTag = ADJ
--> [ { path, terms: [
{
term: "monoterm",
tag: [ "tag", ...],
frequency,
length
},
{
term: "multiterm",
frequency,
length
}, ...
] }, ... ]
[TeeftFilterTags]
tags = NOM
tags = ADJ
--> [ { path, terms: [
{
term: "monoterm",
tag: [ "tag", ...],
frequency,
length
},
{
term: "multiterm",
frequency,
length
}, ...
] }, ... ]
[TeeftRemoveNumbers]
--> [ { path, terms: [
{
term: "monoterm",
tag: [ "tag", ...],
frequency,
length
},
{
term: "multiterm",
frequency,
length
}, ...
] }, ... ]
[TeeftStopWords]
--> [ { path, terms: [
{
term: "monoterm",
tag: [ "tag", ...],
frequency,
length
},
{
term: "multiterm",
frequency,
length
}, ...
] }, ... ]
[TeeftRemoveShortTerms]
--> [ { path, terms: [
{
term: "monoterm",
tag: [ "tag", ...],
frequency,
length
},
{
term: "multiterm",
frequency,
length
}, ...
] }, ... ]
[TeeftRemoveLongTerms]
--> [ { path, terms: [
{
term: "monoterm",
tag: [ "tag", ...],
frequency,
length
},
{
term: "multiterm",
frequency,
length
}, ...
] }, ... ]
[TeeftRemoveWeirdTerms]
--> [ { path, terms: [
{
term: "monoterm",
tag: [ "tag", ...],
frequency,
length
},
{
term: "multiterm",
frequency,
length
}, ...
] }, ... ]
[TeeftSumUpFrequencies]
--> [ { path, terms: [
{
term: "monoterm",
tag: [ "tag", ...],
frequency,
length
},
{
term: "multiterm",
frequency,
length
}, ...
] }, ... ]
[TeeftSpecificity]
sort = true
--> [ { path, terms: [
{
term: "monoterm",
tag: [ "tag", ...],
frequency,
length,
specificity,
},
{
term: "multiterm",
frequency,
length,
specificity
}, ...
] }, ... ]
[TeeftFilterMonoFreq]
--> [ { path, terms: [
{
term: "monoterm",
tag: [ "tag", ...],
frequency,
length,
specificity,
},
{
term: "multiterm",
frequency,
length,
specificity
}, ...
] }, ... ]
[TeeftFilterMultiSpec]
--> [ { path, terms: [
{
term: "monoterm",
tag: [ "tag", ...],
frequency,
length,
specificity,
},
{
term: "multiterm",
frequency,
length,
specificity
}, ...
] }, ... ]
[dump]
indent = trueusage
Table of Contents
- TeeftExtractTerms
- TeeftFilterMonoFreq
- TeeftFilterMultiSpec
- TeeftFilterTags
- TeeftGetFilesContent
- TeeftListFiles
- TeeftNaturalTag
- TeeftRemoveLongTerms
- TeeftRemoveNumbers
- TeeftRemoveShortTerms
- TeeftRemoveWeirdTerms
- TeeftSentenceTokenize
- TeeftSpecificity
- TeeftStopWords
- TeeftSumUpFrequencies
- TeeftTokenize
- TeeftToLowerCase
TeeftExtractTerms
Take an array of objects { path, sentences: [token, tag: ["tag"]]}. Regroup
multi-terms when possible (noun + noun, adjective + noun, etc.), and
computes statistics (frequency, etc.).
Use lang or nounTag, adjTag, but not lang and the others at the same
time. lang is enough to set nounTag and adjTag.
Parameters
langstring language of the terms to extract (enorfr) (optional, default'fr')nounTagstring noun tag (NOMin French,NNin English) (optional, default'NOM')adjTagstring adjective tag (ADJin French,JJin English) (optional, default'ADJ')
Examples
[{
path: '/path/1',
sentences:
[[
{ token: 'elle', tag: ['PRO:per'] },
{ token: 'semble', tag: ['VER'] },
{ token: 'se', tag: ['PRO:per'] },
{ token: 'nourrir', tag: ['VER'] },
{
token: 'essentiellement',
tag: ['ADV'],
},
{ token: 'de', tag: ['PRE', 'ART:def'] },
{ token: 'plancton', tag: ['NOM'] },
{ token: 'frais', tag: ['ADJ'] },
{ token: 'et', tag: ['CON'] },
{ token: 'de', tag: ['PRE', 'ART:def'] },
{ token: 'hotdog', tag: ['UNK'] }
]]
}]Returns any same as input, with term replacing token, length, and
frequency
TeeftFilterMonoFreq
Filter the data, keeping only multiterms and frequent monoterms.
Minimal frequency (minFrequency parameter) has a default value
automatically computed from the number of tokens in the document.
Parameters
multiLimitNumber threshold for being a multiterm (in tokens number) (optional, default2)minFrequencyNumber minimal frequency to be taken as a frequent term (optional, default7)
TeeftFilterMultiSpec
Filter multiterms to keep only multiterms which specificity is higher than multiterms' average specificity.
TeeftFilterTags
Filter the text in input, by keeping only adjectives and names
Parameters
TeeftGetFilesContent
Take an array of file paths as input, and returns a list of
objects containing the path, and the content of each file.
Returns [{path: string, content: string}] Array of { path, content }
TeeftListFiles
Take an array of directory paths as input, a pattern, and returns a list of file paths matching the pattern in the directories from the input.
Parameters
patternString pattern for files (ex: "*.txt") (optional, default"*")
Returns [String] an array of file paths
TeeftNaturalTag
POS Tagger from natural
French pos tagging using natural (and LEFFF resources)
Take an array of documents (objects: { path, sentences: [[]] })
Yield an array of documents (objects:
{
path, sentences: [
[{
token: "token",
tag: [ "tag", ... ]
},
...]
]
})
Parameters
langstring language of the text to tag (possible values:fr,en) (optional, default'en')
Examples
[{
path: "/path/1",
sentences: [{ "token": "dans", "tag": ["prep"] },
{ "token": "le", "tag": ["det"] },
{ "token": "cadre", "tag": ["nc"] },
{ "token": "du", "tag": ["det"] },
{ "token": "programme", "tag": ["nc"] }
},
]
}]TeeftRemoveLongTerms
Remove long terms from documents (longer than 50 characters).
Documents must have a terms key, containing an array of objects with a
term key of type string..
Yields an array of documents with the same structure.
Input:
[{
"path": "/path/to/file.txt",
"terms": [{ "term": "this very long term should really be removed 678901" },
{ "term": "abcd" }]
}]Output:
[{
"path": "/path/to/file.txt",
"terms": [{ "term": "abcd" }]
}]TeeftRemoveNumbers
Remove numbers from the terms of documents (objects { path, terms: [{ term,
...}] }).
Yields an array of documents with the same structure.
TeeftRemoveShortTerms
Remove short terms from documents (shorter than 3 characters).
Documents must have a terms key, containing an array of objects with a
term key of type string..
Yields an array of documents with the same structure.
Input:
[{
"path": "/path/to/file.txt",
"terms": [{ "term": "a" }, { "term": "abcd" }]
}]Output:
[{
"path": "/path/to/file.txt",
"terms": [{ "term": "abcd" }]
}]TeeftRemoveWeirdTerms
Remove terms with too much non-alphanumeric characters.
Documents must have a terms key, containing an array of objects with a
term key of type string..
Yields an array of documents with the same structure.
Input:
[{
"path": "/path/to/file.txt",
"terms": [{ "term": "αβɣδ" }, { "term": "abcd" }]
}]Output:
[{
"path": "/path/to/file.txt",
"terms": [{ "term": "abcd" }]
}]TeeftSentenceTokenize
Segment the data into an array of documents (objects { path, content }).
Yield an array of documents (objects { path, sentences: []})
TeeftSpecificity
Take documents (with a path, an array of terms, each term being an object
{ term, frequency, length[, tag] }).
Process objects containing frequency, add a specificity to each object, and
remove all object with a specificity below average specificity (except when
filter is false).
Can also sort the objects according to their specificity, when sort is
true.
Parameters
langstring language to take into account (optional, default"en")filterBoolean filter below average specificity (optional, defaulttrue)sortBoolean sort objects according to their specificity (optional, defaultfalse)
TeeftStopWords
Filter the text in input, by removing stopwords in token
Parameters
langstring language of the stopwords (enorfr) (optional, default'en')
TeeftSumUpFrequencies
Sums up the frequencies of identical lemmas from different chunks.
TeeftTokenize
Extract tokens from an array of documents (objects { path, sentences: [] }).
Yields an array of documents (objects: { path, sentences: [[]] })
Warning: results are surprising on uppercase sentences, use TeeftToLowerCase
TeeftToLowerCase
Transform strings to lower case.
Parameters
pathArray[string](https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/String) path to the property to modify (optional, default[])