src/Gargantext/Core/Text/Terms.hs

   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 ConstrainedClassMethods #-}
  32 {-# LANGUAGE StandaloneDeriving #-}
  33 {-# LANGUAGE TemplateHaskell   #-}
  34
  35 module Gargantext.Core.Text.Terms
  36   where
  37
  38 import Control.Lens
  39 import Data.HashMap.Strict (HashMap)
  40 import Data.Hashable (Hashable)
  41 import Data.Map.Strict (Map)
  42 import Data.Text (Text)
  43 import Data.Traversable
  44 import GHC.Base (String)
  45 import GHC.Generics (Generic)
  46 import qualified Data.List           as List
  47 import qualified Data.Set            as Set
  48 import qualified Data.Text           as Text
  49 import qualified Data.HashMap.Strict as HashMap
  50 import Gargantext.Core
  51 import Gargantext.Core.Utils (groupWithCounts)
  52 import Gargantext.Core.Text (sentences, HasText(..))
  53 import Gargantext.Core.Text.Terms.Eleve (mainEleveWith, Tries, Token, buildTries, toToken)
  54 import Gargantext.Core.Text.Terms.Mono  (monoTerms)
  55 import Gargantext.Core.Text.Terms.Mono.Stem (stem)
  56 import Gargantext.Core.Text.Terms.Mono.Token.En (tokenize)
  57 import Gargantext.Core.Text.Terms.Multi (multiterms)
  58 import Gargantext.Core.Types
  59 import Gargantext.Database.Prelude (Cmd)
  60 import Gargantext.Database.Query.Table.Ngrams (insertNgrams)
  61 import Gargantext.Database.Query.Table.NgramsPostag (NgramsPostag(..), insertNgramsPostag, np_form, np_lem)
  62 import Gargantext.Database.Schema.Ngrams (Ngrams(..), NgramsType(..), ngramsTerms, text2ngrams, NgramsId)
  63 import Gargantext.Prelude
  64
  65 data TermType lang
  66   = Mono      { _tt_lang :: !lang }
  67   | Multi     { _tt_lang :: !lang }
  68   | MonoMulti { _tt_lang :: !lang }
  69   | Unsupervised { _tt_lang       :: !lang
  70                  , _tt_windowSize :: !Int
  71                  , _tt_ngramsSize :: !Int
  72                  , _tt_model      :: !(Maybe (Tries Token ()))
  73                  }
  74   deriving (Generic)
  75 deriving instance (Show lang) => Show (TermType lang)
  76
  77 makeLenses ''TermType
  78 --group :: [Text] -> [Text]
  79 --group = undefined
  80
  81 -- remove Stop Words
  82 -- map (filter (\t -> not . elem t)) $
  83 ------------------------------------------------------------------------
  84 -- | Sugar to extract terms from text (hidding 'mapM' from end user).
  85 --extractTerms :: Traversable t => TermType Lang -> t Text -> IO (t [Terms])
  86 extractTerms :: TermType Lang -> [Text] -> IO [[TermsWithCount]]
  87 extractTerms (Unsupervised {..}) xs = mapM (terms (Unsupervised { _tt_model = Just m', .. })) xs
  88   where
  89     m' = case _tt_model of
  90       Just m''-> m''
  91       Nothing -> newTries _tt_windowSize (Text.intercalate " " xs)
  92 extractTerms termTypeLang xs = mapM (terms termTypeLang) xs
  93
  94
  95 ------------------------------------------------------------------------
  96 withLang :: (Foldable t, Functor t, HasText h)
  97          => TermType Lang
  98          -> t h
  99          -> TermType Lang
 100 withLang (Unsupervised {..}) ns = Unsupervised { _tt_model = m', .. }
 101   where
 102     m' = case _tt_model of
 103       Nothing -> -- trace ("buildTries here" :: String)
 104                Just $ buildTries _tt_ngramsSize
 105                     $ fmap toToken
 106                     $ uniText
 107                     $ Text.intercalate " . "
 108                     $ List.concat
 109                     $ map hasText ns
 110       just_m -> just_m
 111 withLang l _ = l
 112
 113 ------------------------------------------------------------------------
 114 data ExtractedNgrams = SimpleNgrams   { unSimpleNgrams   :: Ngrams       }
 115                      | EnrichedNgrams { unEnrichedNgrams :: NgramsPostag }
 116   deriving (Eq, Ord, Generic, Show)
 117
 118 instance Hashable ExtractedNgrams
 119
 120 -- | A typeclass that represents extracting ngrams from an entity.
 121 class ExtractNgramsT h
 122   where
 123     extractNgramsT :: HasText h
 124                    => TermType Lang
 125                    -> h
 126                    -> Cmd err (HashMap ExtractedNgrams (Map NgramsType Int, TermsCount))
 127 ------------------------------------------------------------------------
 128 enrichedTerms :: Lang -> PosTagAlgo -> POS -> Terms -> NgramsPostag
 129 enrichedTerms l pa po (Terms ng1 ng2) =
 130   NgramsPostag l pa po form lem
 131     where
 132       form = text2ngrams $ Text.intercalate " " ng1
 133       lem  = text2ngrams $ Text.intercalate " " $ Set.toList ng2
 134
 135 ------------------------------------------------------------------------
 136 cleanNgrams :: Int -> Ngrams -> Ngrams
 137 cleanNgrams s ng
 138       | Text.length (ng ^. ngramsTerms) < s = ng
 139       | otherwise                           = text2ngrams (Text.take s (ng ^. ngramsTerms))
 140
 141 cleanExtractedNgrams :: Int -> ExtractedNgrams -> ExtractedNgrams
 142 cleanExtractedNgrams s (SimpleNgrams   ng) = SimpleNgrams $ (cleanNgrams s) ng
 143 cleanExtractedNgrams s (EnrichedNgrams ng) = EnrichedNgrams $ over np_form (cleanNgrams s)
 144                                                             $ over np_lem  (cleanNgrams s) ng
 145
 146 extracted2ngrams :: ExtractedNgrams -> Ngrams
 147 extracted2ngrams (SimpleNgrams   ng) = ng
 148 extracted2ngrams (EnrichedNgrams ng) = view np_form ng
 149
 150 ---------------------------
 151 insertExtractedNgrams :: [ ExtractedNgrams ] -> Cmd err (HashMap Text NgramsId)
 152 insertExtractedNgrams ngs = do
 153   let (s, e) = List.partition isSimpleNgrams ngs
 154   m1 <- insertNgrams       (map unSimpleNgrams   s)
 155   --printDebug "others" m1
 156
 157   m2 <- insertNgramsPostag (map unEnrichedNgrams e)
 158   --printDebug "terms" m2
 159
 160   let result = HashMap.union m1 m2
 161   pure result
 162
 163 isSimpleNgrams :: ExtractedNgrams -> Bool
 164 isSimpleNgrams (SimpleNgrams _) = True
 165 isSimpleNgrams _                = False
 166
 167 ------------------------------------------------------------------------
 168 -- | Terms from 'Text'
 169 -- 'Mono' : mono terms
 170 -- 'Multi' : multi terms
 171 -- 'MonoMulti' : mono and multi
 172 -- TODO : multi terms should exclude mono (intersection is not empty yet)
 173 terms :: TermType Lang -> Text -> IO [TermsWithCount]
 174 terms (Mono      lang) txt = pure $ monoTerms lang txt
 175 terms (Multi     lang) txt = multiterms lang txt
 176 terms (MonoMulti lang) txt = terms (Multi lang) txt
 177 terms (Unsupervised { .. }) txt = pure $ termsUnsupervised (Unsupervised { _tt_model = Just m', .. }) txt
 178   where
 179     m' = maybe (newTries _tt_ngramsSize txt) identity _tt_model
 180 -- terms (WithList  list) txt = pure . concat $ extractTermsWithList list txt
 181
 182
 183 ------------------------------------------------------------------------
 184 type WindowSize = Int
 185 type MinNgramSize = Int
 186
 187 -- | Unsupervised ngrams extraction
 188 -- language agnostic extraction
 189 -- TODO: newtype BlockText
 190 termsUnsupervised :: TermType Lang -> Text -> [TermsWithCount]
 191 termsUnsupervised (Unsupervised { _tt_model = Nothing }) = panic "[termsUnsupervised] no model"
 192 termsUnsupervised (Unsupervised { _tt_model = Just _tt_model, .. }) =
 193                map (\(t, cnt) -> (text2term _tt_lang t, cnt))
 194              . groupWithCounts
 195              -- . List.nub
 196              . (List.filter (\l' -> List.length l' >= _tt_windowSize))
 197              . List.concat
 198              . mainEleveWith _tt_model _tt_ngramsSize
 199              . uniText
 200 termsUnsupervised _ = undefined
 201
 202
 203 newTries :: Int -> Text -> Tries Token ()
 204 newTries n t = buildTries n (fmap toToken $ uniText t)
 205
 206 -- | TODO removing long terms > 24
 207 uniText :: Text -> [[Text]]
 208 uniText = map (List.filter (not . isPunctuation))
 209         . map tokenize
 210         . sentences       -- TODO get sentences according to lang
 211         . Text.toLower
 212
 213 text2term :: Lang -> [Text] -> Terms
 214 text2term _ [] = Terms [] Set.empty
 215 text2term lang txt = Terms txt (Set.fromList $ map (stem lang) txt)
 216
 217 isPunctuation :: Text -> Bool
 218 isPunctuation x = List.elem x $  (Text.pack . pure)
 219                              <$> ("!?(),;.:" :: String)