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1 {-|
2 Module : Gargantext.Core.Text.Ngrams
3 Description : Ngrams definition and tools
4 Copyright : (c) CNRS, 2017 - present
5 License : AGPL + CECILL v3
6 Maintainer : team@gargantext.org
7 Stability : experimental
8 Portability : POSIX
9
10 An @n-gram@ is a contiguous sequence of n items from a given sample of
11 text. In Gargantext application the items are words, n is a non negative
12 integer.
13
14 Using Latin numerical prefixes, an n-gram of size 1 is referred to as a
15 "unigram"; size 2 is a "bigram" (or, less commonly, a "digram"); size
16 3 is a "trigram". English cardinal numbers are sometimes used, e.g.,
17 "four-gram", "five-gram", and so on.
18
19 Source: https://en.wikipedia.org/wiki/Ngrams
20
21 TODO
22 group Ngrams -> Tree
23 compute occ by node of Tree
24 group occs according groups
25
26 compute cooccurrences
27 compute graph
28
29 -}
30
31 {-# LANGUAGE TemplateHaskell #-}
32 {-# LANGUAGE ConstrainedClassMethods #-}
33
34 module Gargantext.Core.Text.Terms
35 where
36
37 import Control.Lens
38 import Data.HashMap.Strict (HashMap)
39 import Data.Hashable (Hashable)
40 import Data.Map (Map)
41 import Data.Text (Text)
42 import Data.Traversable
43 import GHC.Base (String)
44 import GHC.Generics (Generic)
45 import qualified Data.List as List
46 import qualified Data.Set as Set
47 import qualified Data.Text as Text
48 import qualified Data.HashMap.Strict as HashMap
49 import Gargantext.Core
50 import Gargantext.Core.Text (sentences, HasText(..))
51 import Gargantext.Core.Text.Terms.Eleve (mainEleveWith, Tries, Token, buildTries, toToken)
52 import Gargantext.Core.Text.Terms.Mono (monoTerms)
53 import Gargantext.Core.Text.Terms.Mono.Stem (stem)
54 import Gargantext.Core.Text.Terms.Mono.Token.En (tokenize)
55 import Gargantext.Core.Text.Terms.Multi (multiterms)
56 import Gargantext.Core.Types
57 import Gargantext.Database.Prelude (Cmd)
58 import Gargantext.Database.Query.Table.Ngrams (insertNgrams)
59 import Gargantext.Database.Query.Table.NgramsPostag (NgramsPostag(..), insertNgramsPostag, np_form, np_lem)
60 import Gargantext.Database.Schema.Ngrams (Ngrams(..), NgramsType(..), ngramsTerms, text2ngrams, NgramsId)
61 import Gargantext.Prelude
62
63 data TermType lang
64 = Mono { _tt_lang :: !lang }
65 | Multi { _tt_lang :: !lang }
66 | MonoMulti { _tt_lang :: !lang }
67 | Unsupervised { _tt_lang :: !lang
68 , _tt_windowSize :: !Int
69 , _tt_ngramsSize :: !Int
70 , _tt_model :: !(Maybe (Tries Token ()))
71 }
72 deriving Generic
73
74 makeLenses ''TermType
75 --group :: [Text] -> [Text]
76 --group = undefined
77
78 -- remove Stop Words
79 -- map (filter (\t -> not . elem t)) $
80 ------------------------------------------------------------------------
81 -- | Sugar to extract terms from text (hiddeng mapM from end user).
82 --extractTerms :: Traversable t => TermType Lang -> t Text -> IO (t [Terms])
83 extractTerms :: TermType Lang -> [Text] -> IO [[Terms]]
84
85 extractTerms (Unsupervised l n s m) xs = mapM (terms (Unsupervised l n s (Just m'))) xs
86 where
87 m' = case m of
88 Just m''-> m''
89 Nothing -> newTries n (Text.intercalate " " xs)
90
91 extractTerms termTypeLang xs = mapM (terms termTypeLang) xs
92
93
94 ------------------------------------------------------------------------
95 withLang :: (Foldable t, Functor t, HasText h)
96 => TermType Lang
97 -> t h
98 -> TermType Lang
99 withLang (Unsupervised l n s m) ns = Unsupervised l n s m'
100 where
101 m' = case m of
102 Nothing -> -- trace ("buildTries here" :: String)
103 Just $ buildTries n $ fmap toToken
104 $ uniText
105 $ Text.intercalate " . "
106 $ List.concat
107 $ map hasText ns
108 just_m -> just_m
109 withLang l _ = l
110
111 ------------------------------------------------------------------------
112 data ExtractedNgrams = SimpleNgrams { unSimpleNgrams :: Ngrams }
113 | EnrichedNgrams { unEnrichedNgrams :: NgramsPostag }
114 deriving (Eq, Ord, Generic, Show)
115
116 instance Hashable ExtractedNgrams
117
118 class ExtractNgramsT h
119 where
120 extractNgramsT :: HasText h
121 => TermType Lang
122 -> h
123 -> Cmd err (HashMap ExtractedNgrams (Map NgramsType Int))
124 ------------------------------------------------------------------------
125 enrichedTerms :: Lang -> PosTagAlgo -> POS -> Terms -> NgramsPostag
126 enrichedTerms l pa po (Terms ng1 ng2) =
127 NgramsPostag l pa po form lem
128 where
129 form = text2ngrams $ Text.intercalate " " ng1
130 lem = text2ngrams $ Text.intercalate " " $ Set.toList ng2
131
132 ------------------------------------------------------------------------
133 cleanNgrams :: Int -> Ngrams -> Ngrams
134 cleanNgrams s ng
135 | Text.length (ng ^. ngramsTerms) < s = ng
136 | otherwise = text2ngrams (Text.take s (ng ^. ngramsTerms))
137
138 cleanExtractedNgrams :: Int -> ExtractedNgrams -> ExtractedNgrams
139 cleanExtractedNgrams s (SimpleNgrams ng) = SimpleNgrams $ (cleanNgrams s) ng
140 cleanExtractedNgrams s (EnrichedNgrams ng) = EnrichedNgrams $ over np_form (cleanNgrams s)
141 $ over np_lem (cleanNgrams s) ng
142
143 extracted2ngrams :: ExtractedNgrams -> Ngrams
144 extracted2ngrams (SimpleNgrams ng) = ng
145 extracted2ngrams (EnrichedNgrams ng) = view np_form ng
146
147 ---------------------------
148 insertExtractedNgrams :: [ ExtractedNgrams ] -> Cmd err (HashMap Text NgramsId)
149 insertExtractedNgrams ngs = do
150 let (s, e) = List.partition isSimpleNgrams ngs
151 m1 <- insertNgrams (map unSimpleNgrams s)
152 --printDebug "others" m1
153
154 m2 <- insertNgramsPostag (map unEnrichedNgrams e)
155 --printDebug "terms" m2
156
157 let result = HashMap.union m1 m2
158 pure result
159
160 isSimpleNgrams :: ExtractedNgrams -> Bool
161 isSimpleNgrams (SimpleNgrams _) = True
162 isSimpleNgrams _ = False
163
164 ------------------------------------------------------------------------
165 -- | Terms from Text
166 -- Mono : mono terms
167 -- Multi : multi terms
168 -- MonoMulti : mono and multi
169 -- TODO : multi terms should exclude mono (intersection is not empty yet)
170 terms :: TermType Lang -> Text -> IO [Terms]
171 terms (Mono lang) txt = pure $ monoTerms lang txt
172 terms (Multi lang) txt = multiterms lang txt
173 terms (MonoMulti lang) txt = terms (Multi lang) txt
174 terms (Unsupervised lang n s m) txt = termsUnsupervised (Unsupervised lang n s (Just m')) txt
175 where
176 m' = maybe (newTries n txt) identity m
177 -- terms (WithList list) txt = pure . concat $ extractTermsWithList list txt
178
179
180 ------------------------------------------------------------------------
181 -- | Unsupervised ngrams extraction
182 -- language agnostic extraction
183 -- TODO: remove IO
184 -- TODO: newtype BlockText
185
186 type WindowSize = Int
187 type MinNgramSize = Int
188
189 termsUnsupervised :: TermType Lang -> Text -> IO [Terms]
190 termsUnsupervised (Unsupervised l n s m) =
191 pure
192 . map (text2term l)
193 . List.nub
194 . (List.filter (\l' -> List.length l' >= s))
195 . List.concat
196 . mainEleveWith (maybe (panic "no model") identity m) n
197 . uniText
198 termsUnsupervised _ = undefined
199
200
201
202 newTries :: Int -> Text -> Tries Token ()
203 newTries n t = buildTries n (fmap toToken $ uniText t)
204
205 -- | TODO removing long terms > 24
206 uniText :: Text -> [[Text]]
207 uniText = map (List.filter (not . isPunctuation))
208 . map tokenize
209 . sentences -- TODO get sentences according to lang
210 . Text.toLower
211
212 text2term :: Lang -> [Text] -> Terms
213 text2term _ [] = Terms [] Set.empty
214 text2term lang txt = Terms txt (Set.fromList $ map (stem lang) txt)
215
216 isPunctuation :: Text -> Bool
217 isPunctuation x = List.elem x $ (Text.pack . pure)
218 <$> ("!?(),;.:" :: String)
219
220