Engineers from Japan, North America, Europe, and Turkey compile a number of approaches to example-based machine translation, one of several methods developed over the past decades. After reviewing the historical, technological, and philosophical background, they look at run-time and template-driven approaches, and derivation trees. Among specific topics are formalizing translation memory, clustering transfer rule induction, and finding translation patterns from dependency structures. They expect the primary readership to be researchers and program developers in example- based and other machine translation, cross-linguistic information retrieval, and bilingual text processing. Annotation (c) Book News, Inc., Portland, OR (booknews.com)
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.
