Natural Language Processing for the Semantic Web. Diana Maynard

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Название Natural Language Processing for the Semantic Web
Автор произведения Diana Maynard
Жанр Программы
Серия Synthesis Lectures on the Semantic Web: Theory and Technology
Издательство Программы
Год выпуска 0
isbn 9781627056328



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       Natural Language Processing for the Semantic Web

       Synthesis Lectures on the Semantic Web: Theory and Technology

      Editor

       Ying Ding, Indiana University

       Paul Groth, Elsevier Labs

      Synthesis Lectures on the Semantic Web: Theory and Application is edited by Ying Ding of Indiana University and Paul Groth of Elsevier Labs. Whether you call it the Semantic Web, Linked Data, or Web 3.0, a new generation of Web technologies is offering major advances in the evolution of the World Wide Web. As the first generation of this technology transitions out of the laboratory, new research is exploring how the growing Web of Data will change our world. While topics such as ontology-building and logics remain vital, new areas such as the use of semantics in Web search, the linking and use of open data on the Web, and future applications that will be supported by these technologies are becoming important research areas in their own right. Whether they be scientists, engineers or practitioners, Web users increasingly need to understand not just the new technologies of the Semantic Web, but to understand the principles by which those technologies work, and the best practices for assembling systems that integrate the different languages, resources, and functionalities that will be important in keeping the Web the rapidly expanding, and constantly changing, information space that has changed our lives.

      Topics to be included:

      • Semantic Web Principles from linked-data to ontology design

      • Key Semantic Web technologies and algorithms

      • Semantic Search and language technologies

      • The Emerging “Web of Data” and its use in industry, government and university applications

      • Trust, Social networking and collaboration technologies for the Semantic Web

      • The economics of Semantic Web application adoption and use

      • Publishing and Science on the Semantic Web

      • Semantic Web in health care and life sciences

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      Copyright © 2017 by Morgan & Claypool

      All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means—electronic, mechanical, photocopy, recording, or any other except for brief quotations in printed reviews, without the prior permission of the publisher.

      Natural Language Processing for the Semantic Web

      Diana Maynard, Kalina Bontcheva, and Isabelle Augenstein

       www.morganclaypool.com

      ISBN: 9781627059091 paperback

      ISBN: 9781627056328 ebook

      DOI 10.2200/S00741ED1V01Y201611WBE015

      A Publication in the Morgan & Claypool Publishers series

       SYNTHESIS LECTURES ON THE SEMANTIC WEB: THEORY AND TECHNOLOGY

      Lecture #15

      Series Editors: Ying Ding, Indiana University

      Paul Groth, Elsevier Labs

      Founding Editor Emeritus: James Hendler, Rensselaer Polytechnic Institute

      Series ISSN

      Print 2160-4711 Electronic 2160-472X

       Natural Language Processing for the Semantic Web

      Diana Maynard

      University of Sheffield

      Kalina Bontcheva

      University of Sheffield

      Isabelle Augenstein

      University College London

       SYNTHESIS LECTURES ON THE SEMANTIC WEB: THEORY AND TECHNOLOGY #15

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       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