Mine implicit features using a generative feature language model.
Project description
GFLM: mine implicit features using a generative feature language model
Description
This package implements a Generative Feature Language Models for Mining Implicit Features.
Given the following input:
- a text dataset
- a set of predefined features
Compute the following:
- mapping of explicit and implicit features on the data
- using both gflm_word and gflm_section algorithms
Install
pip install feature_mining
Usage
Usage:
from feature_mining import FeatureMining
fm = FeatureMining()
fm.load_ipod(full_set=False)
fm.fit()
fm.predict()
Results:
- prediction using 'section': fm.gflm.gflm_section
- prediction using 'word': fm.gflm.gflm_word
Package created based on the following paper
S. Karmaker Santu, P. Sondhi and C. Zhai, "Generative Feature Language Models for Mining Implicit Features from Customer Reviews", Proceedings of the 25th ACM International on Conference on Information and Knowledge Management - CIKM '16, 2016.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
feature_mining-0.0.25.tar.gz
(295.0 kB
view hashes)
Built Distribution
Close
Hashes for feature_mining-0.0.25-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 3bff2a6594d355534ee7acf989eb0466f2b130c98c4b031181477c502d05aec6 |
|
MD5 | 9ce3f7cd8f94cea27163d99f1a5ce248 |
|
BLAKE2b-256 | 9507c44d24f9c94a9f59195cb01ec93ce25a4cd5347ef2adfc7456e3c1f5d572 |