ka-ve_summarify

Takım Üyeleri

• Yunus Emre Gündoğmuş
• Feyza Zeynep Salam
• Emre Yüksel
• Büşra Gökmen
• Hasan Kemik

Kullanım

Gerekli Kütüphaneler

import pandas as pd
import numpy as np
from nltk.corpus import stopwords
import heapq
from gensim.summarization import keywords
from nltk import sent_tokenize
from sklearn.metrics.pairwise import cosine_similarity
from gensim.models import KeyedVectors
import networkx as nx
import re
import numpy as np
import json
import pickle
from keras.models import model_from_json
from keras.models import load_model
import Extraction_Based_Text_Summarization

Yukarıdaki kütüphaneleri programınıza ekledikten sonra,

ex_sum = extraction_based_sum()

kodu ile class'ı çağırabilir. Sonrasında elinizde özetlenmesini istediğiniz veri ile

ex_sum.get_sentences(text,k)

k kadar cümleyi metinden alabilirsiniz. Anahtar kelime çıkarımı için ise,

ex_sum.get_keywords(text,ratio)

kodunu kullanarak, metindeki kelime sayısının oranı kadar anahtar kelime alabilirsiniz. Bu sayıyı ratio değeri ile kontrol edebilirsiniz.

Referanslar

• [1] https://github.com/deeplearningturkiye/kelime_kok_ayirici
• [2] https://github.com/akoksal/Turkish-Word2Vec
• [3] https://github.com/Eruimdas/turkish_text_summarization
• [4] https://tscorpus.com

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Team Members

• Yunus Emre Gündoğmuş
• Feyza Zeynep Salam
• Emre Yüksel
• Büşra Gökmen
• Hasan Kemik

How to use

Necessary Libraries

import pandas as pd
import numpy as np
from nltk.corpus import stopwords
import heapq
from gensim.summarization import keywords
from nltk import sent_tokenize
from sklearn.metrics.pairwise import cosine_similarity
from gensim.models import KeyedVectors
import networkx as nx
import re
import numpy as np
import json
import pickle
from keras.models import model_from_json
from keras.models import load_model
import Extraction_Based_Text_Summarization

After you've added those libraries,

ex_sum = extraction_based_sum()

you can use the class with that code, and after that, with the text you want to be summarized,

ex_sum.get_sentences(text,k)

you can take the best k sentences from it. For keyword extraction,

ex_sum.get_keywords(text,ratio)

with the code above, you can get keywords according to the ratio of the word count in the text. You can control that by changing ratio value.

References

• [1] https://github.com/deeplearningturkiye/kelime_kok_ayirici
• [2] https://github.com/akoksal/Turkish-Word2Vec
• [3] https://github.com/Eruimdas/turkish_text_summarization
• [4] https://tscorpus.com