Alignment-Based Learning (ABL) is a symbolic grammar inference framework that has succesfully 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. For more information, see the reference list at the end of this file.
This package contains a C++ implementation of ABL. It is maintained by:
Menno van Zaanen ([email protected])
The latest version of this package can be found on:
http://ilk.uvt.nl/~menno/research/software/abl
For any questions, remarks, bugs, improvements, or any other matters of concern about this package, send an email to: [email protected]
Please read the following before using this ABL package:
LICENCE : conditions and terms for using this software INSTALL : information on installing this software
The ABL package should run on any standard UNIX based platform. It requires a C++ compiler (> GCC 3.0).
The ABL package was developed by Menno van Zaanen (Tilburg University, The Netherlands) and Jeroen Geertzen (University of Cambridge, UK). The project was partially supported financially with a grant from Macquarie University, Australia.
[1] "Bootstrapping Structure into Language: Alignment-Based Learning", Menno van Zaanen, 2001, PhD Thesis, School of Computing, University of Leeds, UK.
[2] "Implementing Alignment-Based Learning", Menno van Zaanen, 2002, In: Proceedings of the International Colloquium on Grammatical Inference (ICGI), pp 312-314, Amsterdam, the Netherlands.
[3] "String alignment in grammatical inference: what suffix trees can do", Jeroen Geertzen, 2003, Technical report ILK-0311, Tilburg University, The Netherlands.