Current Trends in Parsing Technology

Chapter
Part of the Text, Speech and Language Technology book series (TLTB, volume 43)

Abstract

Significant advances in natural language processing require the development of adaptive syterns both for spoken and written language: systems that can interact naturally with human users, extend easily to new domains, produce readily usable translations of several languages, search the web rapidly and accurately, surnrnarise news coherently, and detect shifts in moods and emotions. Recent statistical datadriven techniques in natural language processing aim at acquiring the needed adaptivity by modelling the syntactic and lexical properties of large quantities of naturally occurring text.

Keywords

Natural Language Processing Machine Translation Semantic Representation Domain Adaptation Latent Variable Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media B.V. 2010

Authors and Affiliations

  1. 1.University of GenevaGenevaSwitzerland
  2. 2.Tilburg Center for Cognition and Communication (TiCC) and Department of Communication and Information SciencesTilburg UniversityTilburgThe Netherlands
  3. 3.Uppsala UniversityUppsalaSweden

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