Fatick Stemmer

Description

Orginal Authors main focus was to program a light-weight library to determine a identical word for same type of inflected word as stem to run on any model. Currently, generated stems efficacy for Data analysis and NLP tasks is yet to be determined.

Installation

Run the following to install:

• using git

git clone https://github.com/SaifurOWL/Bangla-stemmer-Usable-Variant-for-self.git
cd Bangla-stemmer-Usable-Variant-for-self
python setup.py install

• for colab (cloning to colabs own drive)

!git clone https://github.com/SaifurOWL/Bangla-stemmer-Usable-Variant-for-self.git
%cd /content/Bangla-stemmer-Usable-Variant-for-self
!python setup.py install

Usages

Example 01:

from bangla_stemmer.stemmer import stemmer
wordlist = ['কবিরগুলিকে', 'আমাকে', 'নামাবার']
stmr = stemmer.BanglaStemmer()
stm = stmr.stem(word)
print(stm)

output: ['কবির', 'আমা', 'নামা']

Example 01:

from bangla_stemmer.stemmer.stemmer import BanglaStemmer
word = 'কবিরগুলিকে'
stm = BanglaStemmer().stem(word)
print(stm)

output: ['কবির', 'আমা', 'নামা']

Grammar Rule

The grammar rules applied here are based on the algorithm of Rafi Kamal. However some major and required modification has been made in this library in order to make it compatible with any model.  

Reference:    ⮑ BanglaKit