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Get Free Ebook Recognizing Textual Entailment: Models and Applications (Synthesis Lectures on Human Language Technologies)

Get Free Ebook Recognizing Textual Entailment: Models and Applications (Synthesis Lectures on Human Language Technologies)

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Recognizing Textual Entailment: Models and Applications (Synthesis Lectures on Human Language Technologies)

Recognizing Textual Entailment: Models and Applications (Synthesis Lectures on Human Language Technologies)


Recognizing Textual Entailment: Models and Applications (Synthesis Lectures on Human Language Technologies)


Get Free Ebook Recognizing Textual Entailment: Models and Applications (Synthesis Lectures on Human Language Technologies)

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Recognizing Textual Entailment: Models and Applications (Synthesis Lectures on Human Language Technologies)

About the Author

Ido Dagan, Bar Ilan University, IsraelDan Roth, University of Illinois, UrbanaMark Sammons, University of Illinois, UrbanaFabio Zanzotto, University of Rome "Tor Vergata," Italy

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Product details

Series: Synthesis Lectures on Human Language Technologies (Book 23)

Paperback: 220 pages

Publisher: Morgan & Claypool Publishers; 1 edition (July 1, 2013)

Language: English

ISBN-10: 1598298348

ISBN-13: 978-1598298345

Product Dimensions:

7.5 x 0.5 x 9.2 inches

Shipping Weight: 1.1 pounds (View shipping rates and policies)

Average Customer Review:

5.0 out of 5 stars

1 customer review

Amazon Best Sellers Rank:

#3,947,410 in Books (See Top 100 in Books)

Recognizing textual entailment is the task of determining when one piece of text entails or implies the meaning of another: for example, that “She complains of chest discomfort after meals” entails that “She experiences chest discomfort”, but not that “She has been diagnosed with acid reflux disease.” This book describes techniques for using computers to recognize textual entailment. As the book demonstrates, being able to do this is helpful for teaching computers to answer questions, summarize documents, find information, and other things.The book is exceptionally clearly written, and gives comprehensible explanations of a number of phenomena that make the task difficult, as well as a variety of approaches to performing the task. These include alignment and edit distance, transformations, logical inference, and combinations of these. Recognizing textual entailment requires a variety of different kinds of knowledge, including knowledge about language and knowledge about the world, and a full chapter is devoted to sources of such knowledge. A set of case studies gives detailed descriptions of a number of systems that have been produced to tackle the task, including side-by-side comparisons of the approaches and their results.The book includes discussions of how to evaluate computer programs that attempt to recognize textual entailment. A number of standard data sets for the task are described in terms of how they were made, what kinds of metrics are most appropriate for measuring performance on them, and what kinds of other tasks they can support.As mentioned above, the book is quite clearly written, and even a pleasure to read. It offers as much overview as a beginner would need to get started in the field, and as much detail as an expert would need to replicate or extend prior research in their own work.

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Recognizing Textual Entailment: Models and Applications (Synthesis Lectures on Human Language Technologies) PDF
Recognizing Textual Entailment: Models and Applications (Synthesis Lectures on Human Language Technologies) PDF

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