AnyStyle is a very fast and smart parser for academic references. It was originally inspired by ParsCit and FreeCite; AnyStyle uses machine learning algorithms and aims to make it easy to train the model with data that is relevant to your parsing needs.
$ [sudo] gem install anystyle-cli
$ anystyle --help
$ anystyle help find
$ anystyle help parse
See anystyle-cli for more details.
Install the anystyle gem.
$ [sudo] gem install anystyle
Once installed, you can use the static Parser and Finder instances
by calling the AnyStyle.parse or AnyStyle.find methods. For example:
require 'anystyle'
pp AnyStyle.parse 'Derrida, J. (1967). L’écriture et la différence (1 éd.). Paris: Éditions du Seuil.'
#-> [{
# :author=>[{:family=>"Derrida", :given=>"J."}],
# :date=>["1967"],
# :title=>["L’écriture et la différence"],
# :edition=>["1"],
# :location=>["Paris"],
# :publisher=>["Éditions du Seuil"],
# :language=>"fr",
# :scripts=>["Common", "Latin"],
# :type=>"book"
#}]Alternatively, you can create your own AnyStyle::Parser or
AnyStyle::Finder with custom options.
AnyStyle is available as web application at anystyle.io.
The web application is open source and you can also host yourself!
You can train custom Finder and Parser models. To do this, you need to prepare your own data sets for training. You can create your own data from scratch or build on AnyStyle's default sets. The default parser model is based on the core data set; the default finder model source data is not publicly available in its entirety, but you can find a number of tagged documents here.
When you have compiled a data set for training, you will be ready to create your own model:
$ anystyle train training-data.xml custom.mod
This will save your new model as custom.mod. To use your model
instead of AnyStyle's default, use the -P or --parser-model flag
and, respectively, -F or --finder-model to use a custom Finder
model. For instance, the command below would parse all references
in bib.txt using the custom model we just trained and print the
result to STDOUT using the JSON output format:
$ anystyle -P custom.mod -f json parse bib.txt -
When training your own models, it is good practice to check the quality using a second data set. For example, using AnyStyle's own gold data set (a large, manually curated data set) we could check our custom model like this:
$ anystyle -P x.mod check ./res/parser/gold.xml
Checking gold.xml................. 1 seq 0.06% 3 tok 0.01% 3s
This command will print the sequence and token error rates; in the case of AnyStyle a the number of sequence errors is the number of references which were tagged differently by the parser than they were in the input; the number of token errors is the total number of words across all the references which were tagged differently. In the example above, we got one reference wrong (out of 1700 at the time); but even this one reference was mostly tagged correctly, because only a total of 3 words were tagged differently.
When working with training data, it is a good idea to use the
Wapiti::Dataset API in Ruby: it supports all the standard set
operators and makes it very easy to combine or compare data sets.
During the statistical analysis of reference strings, AnyStyle relies
on a large feature dictionary; by default, AnyStyle creates a persistent
Ruby Hash in the folder of the anystyle-data Gem. This uses up about
2MB of disk space and keeps the entire dictionary in memory. If you prefer
a smaller memory footprint, you can alternatively use AnyStyle's GDBM
dictionary. GDBM bindings are part of the Ruby standard library and are
supported on all platforms, but you may have to install GDBM on your
platform before installing Ruby.
If you do not want to use the the persistent Ruyb Hash nor the GBDM bindings, you can store your dictionary in memory (not recommended) or use a Redis. The best way to change the default dictionary adapter is by adjusting AnyStyle's default configuration (when using the default parser instances you must set the default before using the parser):
AnyStyle::Dictionary.defaults[:adapter] = :ruby
#-> Use a persistent Ruby hash;
#-> slower start-up than GDBM but no extra dependency
AnyStyle::Dictionary.defaults[:adapter] = :hash
#-> Use in-memory dictionary; slow start-up but uses no space on disk
require 'anystyle/dictionary/gdbm'
AnyStyle::Dictionary.defaults[:adapter] = :gdbm
To use Redis, install the redis and redis/namespace (optional) Gems
and configure AnyStyle to use the Redis adapter:
AnyStyle::Dictionary.defaults[:adapter] = :redis
# Adjust the Redis-specifi configuration
require 'anystyle/dictionary/redis'
AnyStyle::Dictionary::Redis.defaults[:host] = 'localhost'
AnyStyle::Dictionary::Redis.defaults[:port] = 6379
The AnyStyle source code is hosted on GitHub. You can check out a copy of the latest code using Git:
$ git clone https://github.com/inukshuk/anystyle.git
If you've found a bug or have a question, please open an issue on the AnyStyle issue tracker. Or, for extra credit, clone the AnyStyle repository, write a failing example, fix the bug and submit a pull request.
AnyStyle is a volunteer effort and we encourage you to join us! Over the years our main contributors have been:
Copyright 2011-2020 Sylvester Keil. All rights reserved.
AnyStyle is distributed under a BSD-style license. See LICENSE for details.