Trends in Parsing Technology Dependency Parsing, Domain Adaptation, and Deep Parsing /

• Corporate Author: SpringerLink (Online service)
• Other Authors: Bunt, Harry. (Editor), Merlo, Paola. (Editor), Nivre, Joakim. (Editor)
• Format: Electronic
• Language: English
• Published: Dordrecht : Springer Netherlands : Imprint: Springer, 2010.
• Series: Text, Speech and Language Technology, 43
• Subjects: Linguistics.; Translators (Computer programs).; Computational linguistics.; Computational Linguistics.; Language Translation and Linguistics.
• Online Access: https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-90-481-9352-3

Parsing technology is a central area of research in the automatic processing of human language. It is concerned with the decomposition of complex structures into their constituent parts, in particular with the methods, the tools and the software to parse automatically. Parsers are used in many appli...

Table of Contents:

• Current Trends in Parsing Technology
• Single Malt or Blended?
• A Latent Variable Model for Generative Dependency Parsing
• Dependency Parsing and Domain Adaption with Data-Driven LR Models and Parser Ensembles
• Dependency Parsing Using Global Features
• Dependency Parsing with Second-Order Feature Maps and Annotated Semantic Information
• Strictly Lexicalised Dependency Parsing
• Favor Short Dependencies
• Corrective Dependency Parsing.-Inducing Lexicalised PCFGs with Latent Heads
• Self-Trained Bilexical Preferences to Improve Disambiguation Accuracy
• Are Very Large Context-Free Grammars Tractable?
• Efficiency in Unification-Based N-Best Parsing
• HPSG Parsing with a Supertagger.-Evaluating the Impact of Re-training a Lexical Disambiguation Model on Domain Adaption of an HPSG Parser.-Semi-supervised Training of a Statistical Parser from Unlabeled Partially-bracketed Data
• Index.