An extension for asreview implements a version of the tf-idf feature extractor that saves the matrix and the vocabulary.

Related tags

Text Data & NLP asreview-extension-vocab-extractor
Overview

Extension - matrix and vocabulary extractor for TF-IDF and Doc2Vec

An extension for ASReview that adds a tf-idf extractor that saves the matrix and the vocabulary to pickle and JSON respectively, and a doc2vec extractor that grabs the entire doc2vec model. Requested in discussion post #650.

Getting started

Install the new classifier with:

pip install .

or

python -m pip install git+https://github.com/asreview/asreview-extension-vocab-extractor.git

Usage

Run the simulation as usual, but this time use tfidf_grab or doc2vec_grab as feature extractor. Extracts the matrix and the vocabulary during simulation preparation. The new Feature extractor tfidf_grab is defined in asreviewcontrib.models.tfidf_grab.py, and doc2vec_grab is defined in asreviewcontrib.models.doc2vec_grab.py.

The new tf-idf extractor can be used like this:

asreview simulate benchmark:van_de_Schoot_2017 --state_file myreview.h5 -e tfidf_grab

The vocabulary is saved to the current folder as vocabulary.json, and the matrix is pickled to matrix.pickle.

NOTE Extracting the pickle can be done like this:

import pickle

matrix = pickle.load(open("matrix.pickle","rb"))
print(matrix.shape)

The new doc2vec extractor can be used like this, assuming gensim is installed:

asreview simulate benchmark:van_de_Schoot_2017 --state_file myreview.h5 -e doc2vec_grab

The doc2vec extractor will store the entire model to gensim.model. As this might be a difficult file to work with, included in the repo is the file example_doc2vec.ipynb. This notebook contains code that transforms the gensim model to a dict object with words and their corresponding vector.

Contact

The best resources to find an answer to your question or ways to get in contact are:

License

Apache-2.0

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