Computing Meaning, 1st Edition

  • Published By:
  • ISBN-10: 940077284X
  • ISBN-13: 9789400772847
  • DDC: 401.430285
  • Grade Level Range: College Freshman - College Senior
  • 260 Pages | eBook
  • Original Copyright 2014 | Published/Released June 2014
  • This publication's content originally published in print form: 2014

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This book is a collection of papers by leading researchers in computational semantics. It presents a state-of-the-art overview of recent and current research in computational semantics, including descriptions of new methods for constructing and improving resources for semantic computation, such as WordNet, VerbNet, and semantically annotated corpora. It also presents new statistical methods in semantic computation, such as the application of distributional semantics in the compositional calculation of sentence meanings. Computing the meaning of sentences, texts, and spoken or texted dialogue is the ultimate challenge in natural language processing, and the key to a wide range of exciting applications. The breadth and depth of coverage of this book makes it suitable as a reference and overview of the state of the field for researchers in Computational Linguistics, Semantics, Computer Science, Cognitive Science, and Artificial Intelligence. ‚Äč

Table of Contents

Front Cover.
Half Title Page.
Other Frontmatter.
Title Page.
Copyright Page.
1: Computing Meaning: Annotation, Representation, and Inference.
2: Semantic Representation and Compositionality.
3: Deterministic Statistical Mapping of Sentences to Underspecified Semantics.
4: A Formal Approach to Linking Logical Form and Vector-Space Lexical Semantics.
5: Annotations that Effectively Contribute to Semantic Interpretation.
6: Concrete Sentence Spaces for Compositional Distributional Models of Meaning.
7: Inference and Understanding.
8: Recognizing Textual Entailment and Computational Semantics.
9: Abductive Reasoning with a Large Knowledge Base for Discourse Processing.
10: Natural Logic and Natural Language Inference.
11: Designing Efficient Controlled Languages for Ontologies.
12: Semantic Resources and Annotation.
13: A Context-Change Semantics for Dialogue Acts.
14: VerbNet Class Assignment as a WSD Task.
15: Annotation of Compositional Operations with GLML.
16: Incremental Recognition and Prediction of Dialogue Acts.