Automatic syntactic analysis based on selectional preferences / Alexander Gelbukh, Hiram Calvo.
2018
QA76.9.N38
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Details
Title
Automatic syntactic analysis based on selectional preferences / Alexander Gelbukh, Hiram Calvo.
ISBN
9783319740546 (electronic book)
3319740547 (electronic book)
9783319740539
3319740539
3319740547 (electronic book)
9783319740539
3319740539
Published
Cham, Switzerland : Springer, 2018.
Language
English
Description
1 online resource.
Item Number
10.1007/978-3-319-74054-6 doi
Call Number
QA76.9.N38
Dewey Decimal Classification
006.3/5
410
410
Summary
This book describes effective methods for automatically analyzing a sentence, based on the syntactic and semantic characteristics of the elements that form it. To tackle ambiguities, the authors use selectional preferences (SP), which measure how well two words fit together semantically in a sentence. Today, many disciplines require automatic text analysis based on the syntactic and semantic characteristics of language and as such several techniques for parsing sentences have been proposed. Which is better? In this book the authors begin with simple heuristics before moving on to more complex methods that identify nouns and verbs and then aggregate modifiers, and lastly discuss methods that can handle complex subordinate and relative clauses. During this process, several ambiguities arise. SP are commonly determined on the basis of the association between a pair of words. However, in many cases, SP depend on more words. For example, something (such as grass) may be edible, depending on who is eating it (a cow?). Moreover, things such as popcorn are usually eaten at the movies, and not in a restaurant. The authors deal with these phenomena from different points of view.
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Includes bibliographical references.
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text file PDF
Source of Description
Description based on print version record.
Added Author
Calvo, Hiram, author.
Series
Studies in computational intelligence ; v. 765.
Available in Other Form
Automatic syntactic analysis based on selectional preferences.
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Table of Contents
Introduction
First approach: sentence analysis using rewriting rules
Second approach: constituent grammars
Third approach: dependency trees
Evaluation of the dependency parser
Applications
Prepositional phrase attachment disambiguation
The unsupervised approach: grammar induction
Multiple argument handling
The need for full co-occurrence.
First approach: sentence analysis using rewriting rules
Second approach: constituent grammars
Third approach: dependency trees
Evaluation of the dependency parser
Applications
Prepositional phrase attachment disambiguation
The unsupervised approach: grammar induction
Multiple argument handling
The need for full co-occurrence.