Machine Translation: From Research to Real Users 5th Conference of the Association for Machine Translation in the Americas, AMTA 2002 Tiburon, CA, USA, October 6-12, 2002. Proceedings /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Richardson, Stephen D. (Επιμελητής έκδοσης, http://id.loc.gov/vocabulary/relators/edt)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2002.
• Έκδοση: 1st ed. 2002.
• Σειρά: Lecture Notes in Artificial Intelligence ; 2499
• Θέματα: Natural language processing (Computer science).; Translation and interpretation.; Artificial intelligence.; Mathematical logic.; Natural Language Processing (NLP).; Translation.; Artificial Intelligence.; Mathematical Logic and Formal Languages.

 AMTA 2002: From Research to Real Users Ever since the showdown between Empiricists and Rationalists a decade ago at TMI 92, MT researchers have hotly pursued promising paradigms for MT, including da- driven approaches (e.g., statistical, example-based) and hybrids that integrate these with more traditional rule-based components. During the same period, commercial MT systems with standard transfer archit- tures have evolved along a parallel and almost unrelated track, increasing their cov- age (primarily through manual update of their lexicons, we assume) and achieving much broader acceptance and usage, principally through the medium of the Internet. Webpage translators have become commonplace; a number of online translation s- vices have appeared, including in their offerings both raw and postedited MT; and large corporations have been turning increasingly to MT to address the exigencies of global communication. Still, the output of the transfer-based systems employed in this expansion represents but a small drop in the ever-growing translation marketplace bucket. 

 Technical Papers -- Automatic Rule Learning for Resource-Limited MT -- Toward a Hybrid Integrated Translation Environment -- Adaptive Bilingual Sentence Alignment -- DUSTer: A Method for Unraveling Cross-Language Divergences for Statistical Word-Level Alignment -- Text Prediction with Fuzzy Alignments -- Efficient Integration of Maximum Entropy Lexicon Models within the Training of Statistical Alignment Models -- Using Word Formation Rules to Extend MT Lexicons -- Example-Based Machine Translation via the Web -- Handling Translation Divergences: Combining Statistical and Symbolic Techniques in Generation-Heavy Machine Translation -- Korean-Chinese Machine Translation Based on Verb Patterns -- Merging Example-Based and Statistical Machine Translation: An Experiment -- Classification Approach to Word Selection in Machine Translation -- Better Contextual Translation Using Machine Learning -- Fast and Accurate Sentence Alignment of Bilingual Corpora -- Deriving Semantic Knowledge from Descriptive Texts Using an MT System -- Using a Large Monolingual Corpus to Improve Translation Accuracy -- Semi-automatic Compilation of Bilingual Lexicon Entries from Cross-Lingually Relevant News Articles on WWW News Sites -- Bootstrapping the Lexicon Building Process for Machine Translation between 'New' Languages -- User Studies -- A Report on the Experiences of Implementing an MT System for Use in a Commercial Environment -- Getting the Message In: A Global Company's Experience with the New Generation of Low-Cost, High Performance Machine Translation Systems -- An Assessment of Machine Translation for Vehicle Assembly Process Planning at Ford Motor Company -- System Descriptions -- Fluent Machines' EliMT System -- LogoMedia TRANSLATE™, Version 2.0 -- Natural Intelligence in a Machine Translation System -- Translation by the Numbers: Language Weaver -- A New Family of the PARS Translation Systems -- MSR-MT: The Microsoft Research Machine Translation System -- The NESPOLE! Speech-to-Speech Translation System -- The KANTOO MT System: Controlled Language Checker and Lexical Maintenance Tool -- Approaches to Spoken Translation.