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--- TURBOTOPICS ---
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(C) Copyright 2009, David M. Blei ([email protected])
This file is part of TURBOTOPICS.
TURBOTOPICS is free software; you can redistribute it and/or modify it
under the terms of the GNU General Public License as published by the
Free Software Foundation; either version 2 of the License, or (at your
option) any later version.
TURBOTOPICS is distributed in the hope that it will be useful, but
WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
General Public License for more details.
You should have a copy of the GNU General Public License along with
this program; if not, write to the Free Software Foundation, Inc., 59
Temple Place, Suite 330, Boston, MA 02111-1307 USA
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This code contains python scripts for running the TURBOTOPICS method
on either a corpus of documents or a corpus of documents combined with
the output of LDA-C. for both scripts, the corpus is a file of the
original text of documents, one per line.
Note that neither script requires specifying how large N should be in
the N-grams. For more information about the method, see the paper at
http://arxiv.org/abs/0907.1013
The two scripts are
compute_ngrams.py:
Compute recursive multi-word expressions from a corpus. This will
write out a file of vocabulary (including multi-word expressions)
and their counts.
lda_topics.py:
Compute multi-word expressions per-topic from a corpus and LDA-C
fit. (Note: the argument --ntopics is the same as K in LDA-C.)
This will write out a file for each topic with the expressions and
counts. Again, see the paper for details.
Any questions/comments about this code should be posted to the topic
models mailing list. Subscribe at
https://lists.cs.princeton.edu/mailman/listinfo/topic-models
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Turbo topics find significant multiword phrases in topics.
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