28.4136, Books: Natural Language Processing for the Semantic Web: Maynard, Bontcheva, Augenstein

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LINGUIST List: Vol-28-4136. Mon Oct 09 2017. ISSN: 1069 - 4875.

Subject: 28.4136, Books: Natural Language Processing for the Semantic Web: Maynard, Bontcheva, Augenstein

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Date: Mon, 09 Oct 2017 18:13:50
From: David Schlangen [schlangen at morganclaypool.com]
Subject: Natural Language Processing for the Semantic Web: Maynard, Bontcheva, Augenstein

 


Title: Natural Language Processing for the Semantic Web 
Series Title: Synthesis Lectures on the Semantic Web: Theory and Technology edited by Ying Ding and Paul Groth  

Publication Year: 2017 
Publisher: Morgan & Claypool Publishers
	   http://www.morganclaypool.com
	

Book URL: http://www.morganclaypoolpublishers.com/catalog_Orig/product_info.php?products_id=1009 


Author: Diana Maynard
Author: Kalina Bontcheva
Author: Isabelle Augenstein

Electronic: ISBN:  9781627056328 Pages: 194 Price: U.S. $ 60
Paperback: ISBN:  9781627059091 Pages: 194 Price: U.S. $ 75


Abstract:

This book introduces core natural language processing (NLP) technologies to
non-experts in an easily accessible way, as a series of building blocks that
lead the user to understand key technologies, why they are required, and how
to integrate them into Semantic Web applications. Natural language processing
and Semantic Web technologies have different, but complementary roles in data
management. Combining these two technologies enables structured and
unstructured data to merge seamlessly. Semantic Web technologies aim to
convert unstructured data to meaningful representations, which benefit
enormously from the use of NLP technologies, thereby enabling applications
such as connecting text to Linked Open Data, connecting texts to each other,
semantic searching, information visualization, and modeling of user behavior
in online networks.

The first half of this book describes the basic NLP processing tools:
tokenization, part-of-speech tagging, and morphological analysis, in addition
to the main tools required for an information extraction system (named entity
recognition and relation extraction) which build on these components. The
second half of the book explains how Semantic Web and NLP technologies can
enhance each other, for example via semantic annotation, ontology linking, and
population. These chapters also discuss sentiment analysis, a key component in
making sense of textual data, and the difficulties of performing NLP on social
media, as well as some proposed solutions. The book finishes by investigating
some applications of these tools, focusing on semantic search and
visualization, modeling user behavior, and an outlook on the future.
 



Linguistic Field(s): Cognitive Science
                     Computational Linguistics
                     Semantics


Written In: English  (eng)

See this book announcement on our website: 
http://linguistlist.org/pubs/books/get-book.cfm?BookID=120014

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