shorttext is a Python package that facilitates supervised and unsupervised
learning for short text categorization. Due to the sparseness of words and
the lack of information carried in the short texts themselves, an intermediate
representation of the texts and documents are needed before they are put into
any classification algorithm. In this package, it facilitates various types
of these representations, including topic modeling and word-embedding algorithms.
Since release 1.5.2, it runs on Python 3.9.
Since release 1.5.0, support for Python 3.6 was decommissioned.
Since release 1.2.4, it runs on Python 3.8.
Since release 1.2.3, support for Python 3.5 was decommissioned.
Since release 1.1.7, support for Python 2.7 was decommissioned.
Since release 1.0.8, it runs on Python 3.7 with 'TensorFlow' being the backend for
Since release 1.0.7, it runs on Python 3.7 as well, but the backend for
keras cannot be
Since release 1.0.0,
shorttext runs on Python 2.7, 3.5, and 3.6.
gensimtopic models (LDA, LSI, Random Projections) and autoencoder;
Documentation and tutorials for
shorttext can be found here: http://shorttext.rtfd.io/.
To install it, in a console, use
pip install -U shorttext
or, if you want the most recent development version on Github, type
>>> pip install -U git+https://github.com/stephenhky/PyShortTextCategorization@master
Developers are advised to make sure
Keras >=2 be installed. Users are advised to install the backend
Tensorflow (preferred) or
Theano in advance. It is desirable if
Cython has been previously installed too.
See installation guide for more details.
To report any issues, go to the Issues tab of the Github page and start a thread. It is welcome for developers to submit pull requests on their own to fix any errors.
If you would like to contribute, feel free to submit the pull requests. You can talk to me in advance through e-mails or the Issues page.