The 1990s saw a paradigm change in the use of corpus-driven methods in NLP. In the field of multilingual NLP (such as machine translation and terminology mining) this implied the use of parallel corpora. However, parallel resources are relatively scarce: many more texts are produced daily by native speakers of any given language than translated. This situation resulted in a natural drive towards the use of comparable corpora, i.e. non-parallel texts in the same domain or genre. Nevertheless, this research direction has not produced a single authoritative source suitable for researchers and students coming to the field.
The proposed volume provides a reference source, identifying the state of the art in the field as well as future trends. The book is intended for specialists and students in natural language processing, machine translation and computer-assisted translation.
Here is the first comprehensive resource on the use of comparable corpora in multilingual Natural Language Processing, which goes beyond such techniques as such as machine translation and terminology mining to utilize non-parallel texts in the same domain.
Preface - Building and Using Comparable Corpora. S.Sharoff, R.Rapp, P.Zweigenbaum.- Overviewing Important Aspects of the Last 20 Years of Research in Comparable Corpora.- S.Sharoff, R.Rapp, P.Zweigenbaum.- Part I: Compiling and Measuring Comparable Corpora.- Multilingual Corpus Collection. S.Shi, P.Fung.- Automatic Comparable Web Corpora Collection and Bilingual Terminology Extraction for Specialized Dictionary Making. A.Gurrutxaga, I.Leturia, I.San Vicente, X.Saralegi.- Statistical Comparability: Methodological Caveats. R.K?hler.- Methods for Collection and Evaluation of Comparable Documents. M.Lestari Paramita, D.Guthrie, E.Kanoulas, R.Gaizauskas, P.Clough and M.Sanderson.- Measuring the Distance between Comparable Corpora between Lanl"
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