Automatic Syntactic Analysis Based on Selectional Preferences
Authors: Gelbukh, Alexander, Calvo, Hiram
- Describes recent methods for automatically analyzing a sentence, based on the syntactic and semantic characteristics of the elements that form it
- Presents a disambiguation algorithm based on linguistic and semantic knowledge
- Offers new contributions for automatic selectional preferences extraction and its multiple applications
Buy this book
- About this book
-
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.
Buy this book
Services for this Book
Recommended for you
Bibliographic Information
- Bibliographic Information
-
- Book Title
- Automatic Syntactic Analysis Based on Selectional Preferences
- Authors
-
- Alexander Gelbukh
- Hiram Calvo
- Series Title
- Studies in Computational Intelligence
- Series Volume
- 765
- Copyright
- 2018
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer International Publishing AG
- eBook ISBN
- 978-3-319-74054-6
- DOI
- 10.1007/978-3-319-74054-6
- Hardcover ISBN
- 978-3-319-74053-9
- Series ISSN
- 1860-949X
- Edition Number
- 1
- Number of Pages
- VIII, 165
- Topics
