wpli / gensim

Topic Modelling for Humans

Home Page:http://radimrehurek.com/gensim/

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gensim -- Topic Modelling in Python

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Gensim is a Python library for topic modelling, document indexing and similarity retrieval with large corpora. Target audience is the natural language processing (NLP) and information retrieval (IR) community.

Features

  • All algorithms are memory-independent w.r.t. the corpus size (can process input larger than RAM),
  • Intuitive interfaces
    • easy to plug in your own input corpus/datastream (trivial streaming API)
    • easy to extend with other Vector Space algorithms (trivial transformation API)
  • Efficient implementations of popular algorithms, such as online Latent Semantic Analysis (LSA/LSI), Latent Dirichlet Allocation (LDA), Random Projections (RP), Hierarchical Dirichlet Process (HDP) or word2vec deep learning.
  • Distributed computing: can run Latent Semantic Analysis and Latent Dirichlet Allocation on a cluster of computers, and word2vec on multiple cores.
  • Extensive HTML documentation and tutorials.

If this feature list left you scratching your head, you can first read more about the Vector Space Model and unsupervised document analysis on Wikipedia.

Installation

This software depends on NumPy and Scipy, two Python packages for scientific computing. You must have them installed prior to installing gensim.

It is also recommended you install a fast BLAS library before installing NumPy. This is optional, but using an optimized BLAS such as ATLAS or OpenBLAS is known to improve performance by as much as an order of magnitude. On OS X, NumPy picks up the BLAS that comes with it automatically, so you don't need to do anything special.

The simple way to install gensim is:

sudo easy_install gensim

Or, if you have instead downloaded and unzipped the source tar.gz package, you'll need to run:

python setup.py test
sudo python setup.py install

For alternative modes of installation (without root privileges, development installation, optional install features), see the documentation.

This version has been tested under Python 2.6, 2.7 and 3.3.

Documentation

Manual for the gensim package is available in HTML. It contains a walk-through of all its features and a complete reference section. It is also included in the source distribution package.


Gensim is open source software released under the GNU LGPL license. Copyright (c) 2009-2014 Radim Rehurek

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Topic Modelling for Humans

http://radimrehurek.com/gensim/

License:GNU Lesser General Public License v3.0