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Calculating Document Similarity using tfidf and cosinus similarity, Menghitung kemiripan dokumen dengan tf-idf dan cosinus similarity

Jupyter Notebook 79.30% Python 20.70%

documentsimilarity's Introduction

DocumentSimilarity

Calculating Document Similarity using tfidf and cosinus similarity

Menghitung Kemiripan dokumen dengan tf-idf dan cosinus similarity

Dokumen yang akan dibandingkan ada di source1.txt,source2.txt,source3.txt,source4.txt,source5.txt

run di terminal : python feature_extraction.py

Akan menghasilkan hasil kalkulasi di file tf-idf.csv buka menggunakan excel

library yang digunakan di python -sklearn -numpy -Sastrawi.Stemmer

install menggunakan pip

pip install numpy

pip install -U scikit-learn

pip install Sastrawi

Formula yg digunakan :

tf = jumlah terms di dokumen tanpa normalisasi (biasanya dilakukan normalisasi di library) df = jumlah terms di dokumen mana saja yg muncul

formula tfidf yg digunakan sesuai di kelas tf-idf[i,j] = tf[i,j]*log(Ndocument/df[i])

formula cosinus similarity mengmbil konsep perhitungan angle di vector cos(x)=a.b/||a||||b||

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