Buch, Englisch, 139 Seiten, Paperback, Format (B × H): 187 mm x 235 mm
Buch, Englisch, 139 Seiten, Paperback, Format (B × H): 187 mm x 235 mm
Reihe: Synthesis Lectures on Human Language Technologies
ISBN: 978-1-60845-977-3
Verlag: MORGAN & CLAYPOOL
Throughout the text, the key concepts of grammatical inference are interleaved with illustrative examples drawn from problems in computational linguistics. Special attention is paid to the notion of ""learning bias."" In the context of computational linguistics, such bias can be thought to reflect common (ideally universal) properties of natural languages. This bias can be incorporated either by identifying a learnable class of languages which contains the language to be learned or by using particular strategies for optimizing parameter values. Examples are drawn largely from two linguistic domains (phonology and syntax) which span major regions of the Chomsky Hierarchy (from regular to context-sensitive classes). The conclusion summarizes the major lessons and open questions that grammatical inference brings to computational linguistics.
Autoren/Hrsg.
Weitere Infos & Material
- List of Figures
- List of Tables
- Preface
- Studying Learning
- Formal Learning
- Learning Regular Languages
- Learning Non-Regular Languages
- Lessons Learned and Open Problems
- Bibliography
- Author Biographies