Ambiguity Resolution in Language Learning: Computational and Cognitive Models by Hinrich Schütze (PDF)

Description

This volume is concerned with how ambiguity and ambiguity resolution are learned, that is, with the acquisition of the different representations of ambiguous linguistic forms and the knowledge necessary for selecting among them in context. Schütze concentrates on how the acquisition of ambiguity is possible in principle and demonstrates that particular types of algorithms and learning architectures (such as unsupervised clustering and neural networks) can succeed at the task. Three types of lexical ambiguity are treated: ambiguity in syntactic categorisation, semantic categorisation, and verbal subcategorisation. The volume presents three different models of ambiguity acquisition: Tag Space, Word Space, and Subcat Learner, and addresses the importance of ambiguity in linguistic representation and its relevance for linguistic innateness.

User’s Reviews

Product description Book Description This volume is concerned with how ambiguity and ambiguity resolution are learned, that is, with the acquisition of the different representations of ambiguous linguistic forms and the knowledge necessary for selecting among them in context.

Reviews from Amazon users which were colected at the time this book was published on the website:

⭐

⭐

Keywords

Free Download Ambiguity Resolution in Language Learning: Computational and Cognitive Models in PDF format
Ambiguity Resolution in Language Learning: Computational and Cognitive Models PDF Free Download
Download Ambiguity Resolution in Language Learning: Computational and Cognitive Models 1997 PDF Free
Ambiguity Resolution in Language Learning: Computational and Cognitive Models 1997 PDF Free Download
Download Ambiguity Resolution in Language Learning: Computational and Cognitive Models PDF
Free Download Ebook Ambiguity Resolution in Language Learning: Computational and Cognitive Models