generalised-brown
version 1.0 © 2015 Sean Chester and Leon Derczynski
Table of Contents
Introduction
The generalised-brown software suite clusters word types by distributional similarity in two phases. It first generates a list of merges based on the well-known Brown clustering algorithm and then recalls historical states to vary the granularity of the clusters. For example, given the following corpus:
Alice likes dogs and Bob likes cats while Alice hates snakes and Bob hates spiders
Greedily clustering word types based on average mutual information (i.e., running the C++ merge generator) produces the following merge list (assuming a = |V| = 10):
snakes spiders 8
dogs cats 7
Alice Bob 6
and while 5
likes hates 4
dogs snakes 3
dogs and 2
dogs Alice 1
dogs likes 0
One can then recall any historical state of the computation in order to produce a set of clusters (i.e., run the python cluster generator). For example, with c = 5, we recall the state c - 1 = 4 to produce the following clusters:
{snakes, spiders} {dogs, cats} {Alice, Bob} {likes, hates} {and, while}
This approach (setting separate values of a and c) we refer to as Roll-up feature generation. By contrast, traditional Brown clustering would produce the following five clusters (equivalent to running the C++ merge generator with a = 5 and the python cluster generator with c = 5):
{likes, hates} {snakes, spiders, cats, dogs} {and, while} {Alice} {Bob}
For details about the concepts implemented in this software, please read our recent AAAI paper:
L. Derczynski and S. Chester. 2016. "Generalised Brown Clustering and Roll-up Feature Generation." In: Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16). 7 pages. To appear.
For details about traditional Brown clustering, consult the article in which it was introduced:
PF Brown et al. 1992. "Class-based n-gram models of natural language." Computational Linguistics 18(4): 467--479.
or the implementation that our C++ merge generator forked:
Requirements
generalised-brown relies on the following applications:
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For compiling the C++ merge generator: A C++ compiler that is compatible with C++ 11 and OpenMP (e.g., the newest GNU compiler) and the make program
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For running the python cluster generator: A python interpreter
Installation
The python cluster generator does not need to be compiled. To compile the C++ merge generator, navigate to the merge_generator/ subdirectory of the project and type:
make
Usage
To produce a set of features for a corpus, you will first want to use Generalised Brown (i.e., the C++ merge generator) to create a merge list. Then, you can create c clusters by running the python cluster generator on the merge list. This second step can be done for as many values of c as you like, but we recommend that each value of c is not larger than the value of a used to generate the merge list.
To run the C++ merge generator, type:
./merge_generator/wcluster --text [input_file] --a [active_set_size]
The resultant merges will be recorded in:
./[input_file]-c[active_set_size]-p1.out/merges
To run the python cluster generator, type:
python ./cluster_generator/cluster.py -in ./[input_file]-c[active_set_size]-p1.out/merges -c 3
Each word type will be printed to stdout with its cluster id.
The C++ merge generator runs in O(|V| a^2) time, where |V| is the number of distinct word types in the corpus (i.e., the size of the vocabulary) and a is a bound on the algorithm's search space. The python cluster generator runs in O(|V|) time.
License
This software consists of two sub-modules, each released under a different license:
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The python cluster generator is subject to the terms of The MIT License
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The C++ merge generator follows the original licensing terms
of wcluster.
See the relevant sub-directories of this repository for the specific details of each license.
Datasets
You can find aclusters induced from the RCV1 data, including a full merge file, with a=2560, here: http://derczynski.com/sheffield/resources/rcv.a2560.tar.bz2
Contact
This software suite will undergo a major revision; so, you are encouraged to ensure that this is still the latest version. Please do not hesitate to contact the authors if you have comments, questions, or bugs to report.