svectors 0.1.1
==============

svectors is an efficient implementation of dot product computation on sparse
vectors and Jiang/Conrath similarity on the WordNet taxonomy.  At the moment,
there is no documentation for svectors.  Please have a look at the script
"demo.py" to get an idea of how to use it, or consult the source code!

The module "svectors" is the higher-level interface and should be preferred.
"_svectors" is the low-level machinery. It doesn't do much error checking and
it _will_ crash if you provide it with bad parameters.


Installation
------------

Note: You need Python 3.0 or later to run svectors!
To build and install globally run (with appropriate permissions):

$ python3 setup.py install

To install locally (into your home directory or similar) run:

$ python3 setup.py install --user


Copyright and License Information
---------------------------------

Copyright 2010 Hagen Fürstenau <hagenf@coli.uni-saarland.de>
This software is licensed under GPL version 3.
For the license text see the file "COPYING".


Release History
---------------

svectors 0.1.1:
    - corrected copyright comment
    - no changes in functionality

svectors 0.1:
    - initial release
    - efficient dot product and Jiang/Conrath similarity computation

