MOL
Association for Mathematics of Language

MOL is a special interest group of the Association for Computational Linguistics ACL Logo

2013 Meeting on Mathematics of Language

Sofia, Bulgaria
August 9, 2013

Sponsored by
The Association for Mathematics of Language
(A Special Interest Group of the Association for Computational Linguistics (ACL))

MOL2013, the thirteenth Mathematics of Language meeting will be held August 9 2013 in conjunction with ACL 2013, at the National Palace of Culture, Sofia, Bulgaria

Submission

4-page abstracts, ACL2013 formatted, must be submitted through the START system on or before April 26 2013. Notification of acceptance May 24, camera ready copy due June 7th.

Program

On-line program (includes links to draft papers)

Aims And Scope

MoL is devoted to the study of mathematical structures and methods that are of importance to the description of language. Contributions to all areas of this field are welcome. Specific topics within the scope of our 13th meeting include, but are not limited to the following:
  • generative capacity, computational complexity, and learnability of grammar formalisms
  • formal and computational syntax, semantics, pragmatics, and phonology;
  • formal analysis of linguistic theories and frameworks
  • model-theoretic and proof-theoretic methods in linguistics
  • mathematical foundations of statistical and stochastic approaches to language analysis
  • formal models of language use and language change
This year we are actively seeking contributions addressing the theoretical underpinnings of the main tasks and methods of natural language processing, such as speech analysis, (shallow) parsing, POS tagging, named entity recognition, natural language understanding, and machine translation.

Special Events

Invited Speaker: Mark Johnson

Grammars and Topic Models

Context-free grammars have been a cornerstone of theoretical computer science and computational linguistics since their inception over half a century ago. Topic models are a newer development in machine learning that play an important role in document analysis and information retrieval. It turns out there is a surprising connection between the two that suggests novel ways of extending both grammars and topic models. After explaining this connection, I go on to describe extensions which identify topical multi-word collocations and automatically learn the internal structure of named-entity phrases. These new models have applications in text data mining and information retrieval.

MOL Meal Doodle for time and place!

Business Meeting

Proceedings

Camera ready deadline for the procedings is June 7.

Programme Committee

  • Ash Asudeh (Oxford)
  • Alexander Clark (KCL)
  • Anne Foret (IRISA)
  • Gerhard Jaeger (Tubingen)
  • Aravind Joshi (UPenn)
  • Makoto Kanazawa (NII)
  • Andras Kornai (Chair, HAS)
  • Marco Kuhlmann (Co-chair, Uppsala)
  • Andreas Maletti (Stuttgart)
  • Carlos Martin-Vide (Tarragona)
  • Jens Michaelis (Bielefeld)
  • Gerald Penn (Toronto)
  • Carl Polllard (OSU)
  • Geoffrey Pullum (Santa Cruz)
  • James Rogers (Earlham)
  • Giorgio Satta (Padua)
  • Noah Smith (CMU)
  • Ed Stabler (UCLA)
  • Mark Steedman (Edinburgh)
  • Sylvain Salvati (LABRI)
  • Anssi Yli-Jyra (Helsinki)