International Symposium on Data and Sense Mining, Machine Translation and Controlled Languages, and their application to emergencies, and safety critical domains

July 1-3, 2009
University of Franche-Comté
Besançon, France

Keynotes

 

 

Igor Mel’?uk
 

 (University of Montreal)

Title: Formal Models of Natural Language

Igor Mel'cuk was born in Odessa (former USSR, now Ukraine). Ph.D. from the Institute of Linguistics, Academy of Sciences of the USSR, Moscow (Theoretical Problems of Automatic Syntactic Analysis of Texts). Junior, then Senior Research Fellow at the Institute of Linguistics, Academy of Sciences of the USSR, Moscow. Since 1977 full professor, Département de linguistique et de traduction, Université de Montréal. Regular research work under grants from the Social Sciences and Humanities Research Council of Canada and the Quebec Government (eight major grants covering years 1979 through 1995) and smaller grants from the Université de Montréal. Various undergraduate and graduate courses and seminars at different universities and computing centres in the USSR and in the University of California at Los Angeles, Boston University, the University of Delaware at Newark, the University of Melbourne, the University of Canberra, the University of Vienna, the University of Munich, the University of La Coruña, the Russian State University of the Humanities (Moscow), Université de Franche-Comté (Besançon), Université Paris-13 (Villetaneuse), Collège de France, Chaire internationale Blaise-Pascal (École Normale Supérieure, France), University Pompeu Fabra, Barcelona. Main research in General linguistic theory; semantics, syntax, and morphology, and Metalinguistics (linguistic concepts and terminology). I. Mel'cuk has published 38 books, 222 papers. He is Doctor Honoris causa University of Besançon, France, 1977, Member of the Royal Society of Canada, 1994, Professor at the Collège de France (International Chair) 1996-1997, Corresponding Member of the Austrian Academy of Sciences, 1999, Professor of the International Chair Blaise Pascal, École Normale Supérieure, Paris, 2002-2004. He received 1988-1989: Killam Scholarship (Canada), 1989-1990: Guggenheim Fellowship (USA), 1991: Alexander von Humboldt Research Award (Germany), 1997: Award of the French Canadian Association for Advancement of Sciences. He has been at the very beginning of machine translation.
 

Abstract

1. Formal modeling has been for a long time one of the most powerful research tools in science. The time is ripe to develop this technique in the description of natural languages.
2. The Meaning-Text Theory puts forth the Meaning-Text formal model [= MTM] of language—a system of rules that “mimic” the behavior of speakers. More precisely, an MTM specifies the transition from an infinite, but countable set of meanings of language
L to an infinite, but countable set of texts of L.
3. An MTM is based on several multilayer formal representations of utterances at four major levels: semantic, syntactic, morphological, and phonological.
4. An MTM uses dependencies as the main formalism for the description of uttterance structures and leans heavily on a rich semantics-oriented dictionary of a new type: Explanatory Combinatorial Dictionary.

 

 

Makoto Nagao

(Japan)
 

Title : Natural Language Processing in the Internet Age

Dr. Nagao graduated from Graduate School of Engineering, Kyoto University and received his Ph.D in Information Engineering from Kyoto University in 1966.
He was appointed the President of Kyoto University in 1997 and became Emeritus Professor in 2003. He took up the position of President of the National Institute of Information and Communications Technology in 2004 and has been acting as the Librarian of the National Diet Library since April 2007.
He also served as the President of the Japan Association of National Universities; as the founder President of International Association for Machine Translation (IAMT) and the Association for Natural Language Processing (NLP); and as the President of the Institute of Electronics, Information and Communication Engineers (IEICE), Information Processing Society of Japan (IPSJ), and Japan Library Association (JLA).
Dr. Nagao’s research activities cover a variety of topics, including natural language processing, image processing, machine translation, information engineering, and intelligence information science.
His academic contributions were recognized through the IEEE Emanuel R. Piore Award (1993) and the Medal with Purple Ribbon honored by the Japanese Government (1997). He was Japan Prize Laureate in the prize category of Information and Media Technology (2005), and Chevalier de la Legion d'honneur, France (2005).
 

Contents:

1. Importance and availability of linguistic resources
2. Machine translation based on linguistic resources
3. Information search technologies
4. Reliability evaluation of information
5. NLP in the digital library

 
 

John Hutchins

 

(England)

Multiple uses of machine translation and computerised translation tools

W. John Hutchins has published papers and books on linguistics, information retrieval, and in particular machine translation – most are available from his website (http://www.hutchinsweb.me.uk). He is active in the European Association for Machine Translation (president 1995-2004) and the International Association for Machine Translation (president, 1999-2001). Principal works in MT: Machine Translation: Past, Present, Future (Chichester: Ellis Horwood, 1986); An Introduction to Machine Translation [with Harold Somers] (London: Academic Press, 1992); editor of MT News International (1991-1997); editor of Early years in Machine Translation: Memoirs and Biographies of Pioneers (Amsterdam: John Benjamins, 2000); compiler of Compendium of Translation Software (2000 to the present); and compiler of the Machine Translation Archive  (http://www.mt-archive.info) (2004 to the present).

Abstract

For many years MT systems and tools were used principally for the production of good-quality translations: either MT in combination with controlled (restricted) input and/or with human post-editing; or computer-based translation tools by translators. Since 1990 the situation has changed. Corporate use of MT with human assistance has continued to expand (particularly in the area of localisation) and the use of translation aids has increased (particularly with the coming of translation memories). But the main change has been the ever expanding use of unrevised MT output, such as online translation services (Babel Fish, Google, etc.), applications in information extraction, retrieval, intelligence services, news services, electronic mail, and much more. I shall describe the origins, development, current situation and possible futures of multiple usages and applications of computer-based translation technologies.

 

 

Richard Kittredge

(CoGenTex, Inc., USA)

Natural Sublanguages, Controlled Languages, Translation and Generation

Richard Kittredge is founder and President of CoGenTex, Inc., a small business specializing in text generation applications.  He received a Ph.D. in Formal Linguistics and Logic from the University of Pennsylvania in 1969 and served as professor of computational linguistics at the Université de Montréal until 2006.  During 1970-76 he directed the UdeM TAUM project in machine translation, including development of the METEO and AVIATION systems.  In the 1980s and 1990s his research and publications were mainly on sublanguage analysis, and on text generation applied to reports in English and French sublanguages.  He has been a Visiting Scientist at IBM-Japan and at the Australian CSIRO research organization.  

Abstract

Natural sublanguages are linguistic subsystems that arise spontaneously in recurrent situations where humans communicate in limited domains.  With relative clarity of semantics and syntax, they serve as models and reference points in computational linguistics, much as fruit flies serve in genetics research.  We will review some of the lessons learned from past research and applications involving sublanguages of science and technology, and try to extend these insights to current processing applications using statistical methods, including applications involving broader or multiple domains.