Automatic Ambiguity Resolution in Natural Language Processing

An Empirical Approach
1996
ISBN: 978-3-540-62004-4
Verlag: Springer Berlin Heidelberg

Buch, Englisch, 164 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 289 g

Reihe: Lecture Notes in Artificial Intelligence

This is an exciting time for Artificial Intelligence, and for Natural Language Processing in particular. Over the last five years or so, a newly revived spirit has gained prominence that promises to revitalize the whole field: the spirit of empiricism.
This book introduces a new approach to the important NLP issue of automatic ambiguity resolution, based on statistical models of text. This approach is compared with previous work and proved to yield higher accuracy for natural language analysis. An effective implementation strategy is also described, which is directly useful for natural language analysis. The book is noteworthy for demonstrating a new empirical approach to NLP; it is essential reading for researchers in natural language processing or computational linguistics.

Zielgruppe

Research

Autoren/Hrsg.

Franz, Alexander

Fachgebiete

• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Datenanalyse, Datenverarbeitung
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme
• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Grafikprogrammierung
• Mathematik | Informatik EDV | Informatik Informatik Natürliche Sprachen & Maschinelle Übersetzung
• Technische Wissenschaften Elektronik | Nachrichtentechnik Elektronik Robotik
• Mathematik | Informatik EDV | Informatik Informatik Logik, formale Sprachen, Automaten

Inhaltsverzeichnis

Previous work on syntactic ambiguity resolution.- Loglinear models for ambiguity resolution.- Modeling new words.- Part-of-speech ambiguity.- Prepositional phrase attachment disambiguation.- Conclusions.