Schritte International 5 6 Intensivtrainer Mit Audio Cd ❎

Schritte International 5 6 Intensivtrainer Mit Audio Cd ❎



 
 
 
 
 
 
 

Schritte International 5 6 Intensivtrainer Mit Audio Cd

Amazon.com: Schritte International: Intensivtrainer MIT Audio-CD 5 & 6 (Mixed media product)(German) – International [By (author) Daniela Niebisch]: Niebisch, Daniela; Kursbuch-Verlag.
П³à´´Ï„ä, ŐŐÔª ддддд, 2.5”, 2002.
Schritte International: Intensivtrainer MIT Audio-CD 5 & 6 (Mixed media product)(German) – Common [By (author) Daniela Niebisch] on Amazon.com. *FREE* .
International 7 schritte international intensivtrainer mit audio cd 5 6 audiobooks .
www.amazon.com:: Schritte International: Intensivtrainer MIT Audio-CD 5 & 6 (Mixed media product)(German) – Kindle edition by Niebisch, Daniela: “International”, Kindle Store – Free - .
When you’re finished with this FAQ, please .
Anschrift des Herausgebers:
Daniela Niebisch – 52201 Hamburg
eMail : [email protected]
Kindle Store :: Schritte International: Intensivtrainer MIT Audio-CD 5 & 6 (Mixed media product)(German) – Kindle edition by Niebisch, Daniela: “International”.
All the pdf Schritte International: Intensivtrainer MIT Audio-CD 1 & 2 Book ePub Books we offer here is for free reading. our website is a great place to look up any books you want. UNPUBLISHED

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50b96ab0b6

My purpose is to extract the text with the following code:
from nltk.corpus import PlaintextCorpusReader
from nltk.stem.snowballstemmer import SnowballStemmer
import nltk
from nltk.stem import SnowballStemmer

def word_tokenize(s):
return [w.lower() for w in re.split(‘([a-z]+)(?=[A-Z])’, s)]

def stem_to_root(s):
root = ”
if ‘english’ in s:
root = ”
stem = ‘english’
else:
stem = s.stem()
if s.lower() == stem:
root = ”
if root == ”:
root = stem
return root

document = PlaintextCorpusReader(”)

document_text = ‘Öffnen Sie hier Ihre besten Sprachkenntnisse.’

stemmer = SnowballStemmer.load(‘german’)
root_stemmer = SnowballStemmer(‘english’)

document_words = [word_tokenize(i.lower()) for i in document.documents]
document_text =”.join(document_words)

stemmer_word = stem_to_root(document_text)
root_stemmer.stem(stemmer_word)

EDIT
I’ve finally managed to get some code working and read some of the article about stemming.
My work in progress so far:
from nltk.stem.snowballstemmer import SnowballStemmer
import nltk
from nltk import FreqDist

document = PlaintextCorpusReader(‘

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