Title	Recent Advances in Example-Based Machine Translation [electronic resource] / edited by Michael Carl, Andy Way
Imprint	Dordrecht : Springer Netherlands : Imprint: Springer, 2003
Connect to	http://dx.doi.org/10.1007/978-94-010-0181-6
Descript	XXXI, 482 p. online resource

Recent Advances in Example-Based Machine Translation is of relevance to researchers and program developers in the field of Machine Translation and especially Example-Based Machine Translation, bilingual text processing and cross-linguistic information retrieval. It is also of interest to translation technologists and localisation professionals. Recent Advances in Example-Based Machine Translation fills a void, because it is the first book to tackle the issue of EBMT in depth. It gives a state-of-the-art overview of EBMT techniques and provides a coherent structure in which all aspects of EBMT are embedded. Its contributions are written by long-standing researchers in the field of MT in general, and EBMT in particular. This book can be used in graduate-level courses in machine translation and statistical NLP

I Foundations of EBMT -- 1 An Overview of EBMT -- 2 What is Example-Based Machine Translation? -- 3 Example-Based Machine Translation in a Controlled Environment -- 4 EBMT Seen as Case-based Reasoning -- II Run-time Approaches to EBMT -- 5 Formalizing Translation Memory -- 6 EBMT Using DP-Matching Between Word Sequences -- 7 A Hybrid Rule and Example-Based Method for Machine Translation -- 8 EBMT of POS-Tagged Sentences via Inductive Learning -- III Template-Driven EBMT -- 9 Learning Translation Templates from Bilingual Translation Examples -- 10 Clustered Transfer Rule Induction for Example-Based Translation -- 11 Translation Patterns, Linguistic Knowledge and Complexity in EBMT -- 12 Inducing Translation Grammars from Bracketed Alignments -- IV EBMT and Derivation Trees -- 13 Extracting Translation Knowledge from Parallel Corpora -- 14 Finding Translation Patterns from Dependency Structures -- 15 A Best-First Alignment Algorithm for Extraction of Transfer Mappings -- 16 Translating with Examples: The LFG-DOT Models of Translation

1. Computer science
2. Artificial intelligence
3. Computational linguistics
4. Translation and interpretation
5. Computer Science
6. Language Translation and Linguistics
7. Translation
8. Computational Linguistics
9. Artificial Intelligence (incl. Robotics)