A keyphrase extractor for Persian
Project description
Perke
Perke is a Python keyphrase extraction package for Persian language. It provides an end-to-end keyphrase extraction pipeline in which each component can be easily modified or extended to develop new models.
Installation
- The easiest way to install is from PyPI:
pip install perke
Alternatively, you can install directly from GitHub:pip install git+https://github.com/alirezah320/perke.git
- Perke also requires a trained POS tagger model that can be obtained from here and must be put in resources directory.
Simple Example
Perke provides a standardized API for extracting keyphrases from a text. Start
by typing the 4 lines below to use TextRank
keyphrase extractor.
from perke.unsupervised.graph_based import TextRank
# Define the set of valid part of speech tags to occur in the model.
valid_pos_tags = {'N', 'Ne', 'AJ', 'AJe'}
# 1. Create a TextRank extractor.
extractor = TextRank(valid_pos_tags=valid_pos_tags)
# 2. Load the text.
extractor.load_text(input='text or path/to/input_file',
word_normalization_method=None)
# 3. Build the graph representation of the text and weight the
# words. Keyphrase candidates are composed from the 33 percent
# highest weighted words.
extractor.weight_candidates(window_size=2, top_t_percent=0.33)
# 4. Get the 10 highest weighted candidates as keyphrases.
keyphrases = extractor.get_n_best(n=10)
For other models, see the
examples
directory.
Documentation
Documentation and References are available at Read The Docs.
Implemented Models
Perke currently, implements the following keyphrase extraction models:
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