Mernik, Marjan and \v Crepin\v sek, Matej and Gerli\v c, Goran and \v Zumer, Viljem and Bryant, Barrett R. and Sprague, Alan Learning Context-Free Grammars using an Evolutionary Approach 2003 University of Maribor and The University of Alabama at Birginham Machine learning of grammars finds many applications in syntactic pattern recognition, computational biology, natural language acquisition, etc. In this paper a new application of grammatical inference is suggested. Development of domain-specific languages is a hard problem for domain experts not versed in programming language design. We believe that syntax of a small domain-specific language can be inferred from positive and negative programs provided by domain experts. In our work we are the using genetic programming approach in grammatical inference. Grammar-specific heuristic operators and non-random construction of the initial population are proposed to achieve this task. Suitability of the approach is shown by small examples where underlying context-free grammars are successfully inferred. http://www.comp.mq.edu.au/~asloane/plrg/reading/genPar03.pdf machine_learning grammar Christiansen, Henning CHR Grammmars 2002 A grammar formalism based upon CHR is proposed analogously to the way Definite Clause Grammars are defined and implemented on top of Prolog. These grammars execute as robust bottom-up parsers with an inherent treatment of ambiguity and a high flexibility to model various linguistic phenomena... http://www.dat.ruc.dk/~henning/chrg/PapersOnCHRG/index.html constraint_programming grammar prolog Submitted to journal Theory and Practice of Logic Programming Christiansen, Henning User's Guide to CHR Grammars 2002 November \myurlhttp://www.dat.ruc.dk/\~henning/chrg/CHRGusersGuide.html This document explains how to use CHRG which is a grammar notation implemented on top of the CHR language of Constraint Handling Rules. CHR is an extension to Prolog with committed choice multiple-headed rules. You need to have a recent version of SICSTUS Prolog installed on your computer that supports the CHR library. http://www.dat.ruc.dk/\~henning/chrg/CHRGusersGuide.html constraint_programming grammar prolog Visited 28 August 2003 Pullum, Geoffrey K. and Scholz, Barbara C. de Groote, Philippe and Morrill, Glyn and Retoré, Christian On the Distinction between Model-Theoretic and Generative-Enumerative Syntactic Frameworks Proceedings LACL 2001 Springer-Verlag 2001 17-43 Lecture Notes in Artificial Intelligence Berlin Heidelberg Two kinds of framework for stating grammars of natural languages emerged during the 20th century. Here we call them generativeenumerative syntax (GES)an d model-theoretic syntax (MTS). They are based on very different mathematics. GES developed in the 1950s out of Post's work on the syntactic side of logic. MTS arose somewhat later out of the semantic side of logic. We identify some distinguishing theoretical features of these frameworks, relating to cardinality of the set of expressions, size of individual expressions, and �transderivational constraints�. We then turn to three kinds of linguistic phenomena: partial grammaticality, the syntactic properties of expression fragments, and the fact that the lexicon of any natural language is in constant flux, and conclude that MTS has some major advantages for linguistic description that have been overlooked. We briefly consider the issue of what natural languages in MTS terms, and touch on implications for parsing and acquisition. http://www.informatik.uni-trier.de/~ley/db/conf/lacl/lacl2001.html#PullumS01 grammar constraint_programming van Zaanen, Menno ABL: Alignment-Based Learning COLING 2000 - Proceedings of the 18th International Conference on Computational Linguistics 2000 961–967 http://www.ics.mq.edu.au/\~menno/docs/p_coling00.pdf machine_learning grammar van Zaanen, Menno Langley, Pat Bootstrapping Syntax and Recursion using Alignment-Based Learning Proceedings of the Seventeenth International Conference on Machine Learning Morgan Kaufmann Publishers 2000 July 1063–1070 Stanford University http://www.ics.mq.edu.au/\~menno/docs/p_icml00.pdf machine_learning grammar Borsley, Robert D. Modern Phrase Structure Grammar Blackwell 1996 Oxford grammar Bunt, Harry and van Horck, Arthur Discontinuous Constituency Mouton de Gruyer 1996 Berlin grammar Covington, Michael A. GULP 3.1: An Extension of Prolog for Unification-Based Grammar 1994 AI-1994-06 Artificial Intelligence Center, The University of Georgia http://www.ai.uga.edu/\~mc/ NLP grammar prolog McCord, Michael and Bernth, Arendse and Lappin, Shalom and Zadrozny, Wlodek Natural Language Processing within a Slot Grammar Framework International Journal on Artificial Intelligence Tools 1992 1 229-277 2 NLP grammar Carroll, John and Briscoe, Ted and Grover, Claire A Development Environment for Large Natural Language Grammars 1991 Computer Laboratory, University of Cambridge grammar computer Quirk, Randolph and Greenbaum, Sidney and Leech, Geoffrey and Svartvik, Jan A Comprehensive Grammar of the English Language Longman 1985 London grammar Dahl, Öster Some Arguments for Higher Nodes in Syntax: A Reply to Hudson's `Constituency and Dependency' Linguistics 1980 18 484-488 DG grammar Hudson, Richard A Second Attack on Constituency Linguistics 1980 18 489-504 DG grammar Hudson, Richard Constituency and Dependency Linguistics 1980 18 170-198 DG grammar Quirk, Randolph and Greenbaum, Sidney and Leech, Geoffrey and Svartvik, Jan A Grammar of Contemporary English Longman 1972 Harlow, UK grammar Baumgärtner, K. Steger, H. Konstituenz und Dependenz. Zur Integration der beiden grammatischen Prinzipien. Vorschläge für eine strukturale Grammatik des Deutschen Wissenschaftliche Buchgesellschaft 1970 Darmstadt DG grammar Gaifman, H. Dependency Systems and Phrase-Structure Systems Information and Control 1965 8 304-337 DG grammar