papers on "Simple Synchrony Networks" and natural language parsing

Jamie Henderson henders at linc.cis.upenn.edu
Tue Jul 14 16:35:39 EDT 1998


The following two papers on learning natural language parsing using an
architecture that applies Temporal Synchrony Variable Binding to Simple
Recurrent Networks can be retrieved from the following web site:

http://www.dcs.ex.ac.uk/~jamie/

Keywords: Simple Recurrent Networks, variable binding, synchronous
oscillations, natural language, grammar induction, syntactic parsing,
representing structure, systematicity.


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Simple Synchrony Networks: 
Learning to Parse Natural Language with Temporal Synchrony Variable Binding 
Peter Lane and James Henderson
University of Exeter

Abstract:

The Simple Synchrony Network (SSN) is a new connectionist architecture,
incorporating the insights of Temporal Synchrony Variable Binding (TSVB)
into Simple Recurrent Networks.  The use of TSVB means SSNs can output
representations of structures, and can learn generalisations over the
constituents of these structures (as required by systematicity).  This paper
describes the SSN and an associated training algorithm, and demonstrates
SSNs' generalisation abilities through results from training SSNs to parse
real natural language sentences.
(6 pages)

In Proceedings of the 1998 International Conference on Artificial Neural
Networks (ICANN`98), Skovde, Sweden, 1998.


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A Connectionist Architecture for Learning to Parse
James Henderson and Peter Lane
University of Exeter

Abstract:

We present a connectionist architecture and demonstrate that it can learn
syntactic parsing from a corpus of parsed text.  The architecture can
represent syntactic constituents, and can learn generalizations over
syntactic constituents, thereby addressing the sparse data problems of
previous connectionist architectures.  We apply these Simple Synchrony
Networks to mapping sequences of word tags to parse trees.  After training
on parsed samples of the Brown Corpus, the networks achieve precision and
recall on constituents that approaches that of statistical methods for this
task.
(7 pages)

In Proceedings of 17th International Conference on Computational Linguistics
and the 36th Annual Meeting of the Association for Computational Linguistics
(COLING-ACL`98), University of Montreal, Canada, 1998.



-------------------------------
Dr James Henderson
Department of Computer Science
University of Exeter
Exeter EX4 4PT, U.K.
http://www.dcs.ex.ac.uk/~jamie/
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