Software

Alignment-Based Learning (ABL) is a symbolic grammar inference framework that has successfully been applied for several unsupervised machine learning tasks in Natural Language Processing (NLP). Given sequences of symbols only, a system that implements ABL induces structure by aligning and comparing the input sequences. As a result, the input sequences are augmented with the induced structure.

More information on the underlying ABL system and its implementation can be found in the following publications:

Bootstrapping Structure into Language: Alignment-Based Learning
Menno van Zaanen, 2001,
PhD Thesis, School of Computing, University of Leeds, UK.
also www.ics.mq.edu.au/~menno/personal_files/docs/t_leeds.ps.gz

Implementing Alignment-Based Learning
Menno van Zaanen, 2002,
In: Proceedings of the International Colloquium on Grammatical
Inference (ICGI), pp 312-314, Amsterdam, the Netherlands.

String alignment in grammatical inference: what suffix trees can do
Jeroen Geertzen, 2003,
Technical report ILK-0311, Tilburg University, The Netherlands.

The package contains a C++ implementation of ABL as well as a reference guide (in texinfo) and the text of the licence. The package should be easy to install on Linux/UNIX systems (using configure). It is maintained by:

Menno van Zaanen (menno@ics.mq.edu.au)

The latest version of this package can be found on:

www.ics.mq.edu.au/~menno/research/software/abl/

For any questions, remarks, bugs, improvements, or any other matters of concern about this package, send an email to:

menno@ics.mq.edu.au.