Neural Networks for Natural Language Processing

251 Pages·2019·8.952 MB·

by  Sumathi S., Janani M

Neural Networks for
Natural Language
Processing
Sumathi S.
St. Joseph’s College of Engineering, India
Janani M.
St. Joseph’s College of Engineering, India
A volume in the Advances
in Computer and Electrical
Engineering (ACEE) Book Series
Published in the United States of America by
IGI Global
Engineering Science Reference (an imprint of IGI Global)
701 E. Chocolate Avenue
Hershey PA, USA 17033
Tel: [phone]
Fax: [phone]
E-mail: [email protected]
Web site: http://www.igi-global.com
Copyright © 2020 by IGI Global. All rights reserved. No part of this publication may be
reproduced, stored or distributed in any form or by any means, electronic or mechanical, including
photocopying, without written permission from the publisher.
Product or company names used in this set are for identification purposes only. Inclusion of the
names of the products or companies does not indicate a claim of ownership by IGI Global of the
trademark or registered trademark.
Library of Congress Cataloging-in-Publication Data
Names: S., Sumathi, 1979- editor. | M., Janani, 1988- editor.
Title: Neural networks for natural language processing / Sumathi S, Janani
M, editors.
Description: Hershey PA : Engineering Science Reference, [2020] | Includes
bibliographical references and index. | Summary: “This book examines
natural language processing models and algorithms using traditional
symbolic and more recent statistical approaches”-- Provided by
publisher.
Identifiers: LCCN 2019025554 (print) | LCCN 2019025555 (ebook) | ISBN
9781799811596 (h/c) | ISBN 9781799811602 (s/c) | ISBN 9781799811619
(ebook)
Subjects: LCSH: Natural language processing (Computer science) | Neural
networks (Computer science)
Classification: LCC QA76.9.N38 N4785 2020 (print) | LCC QA76.9.N38
(ebook) | DDC 006.3/2--dc23
LC record available at https://lccn.loc.gov/2019025554
LC ebook record available at https://lccn.loc.gov/2019025555

This book is published in the IGI Global book series Advances in Computer and Electrical
Engineering (ACEE) (ISSN: 2327-039X; eISSN: 2327-0403)
British Cataloguing in Publication Data
A Cataloguing in Publication record for this book is available from the British Library.
All work contributed to this book is new, previously-unpublished material.
The views expressed in this book are those of the authors, but not necessarily of the publisher.
For electronic access to this publication, please contact: [email protected].
Advances in Computer
and Electrical Engineering
(ACEE) Book Series
ISSN:2327-039X
EISSN:2327-0403
Editor-in-Chief: Srikanta Patnaik, SOA University, India
Mission
The fields of computer engineering and electrical engineering encompass a broad
range of interdisciplinary topics allowing for expansive research developments
across multiple fields. Research in these areas continues to develop and become
increasingly important as computer and electrical systems have become an integral
part of everyday life.
The Advances in Computer and Electrical Engineering (ACEE) Book Series
aims to publish research on diverse topics pertaining to computer engineering
and electrical engineering. ACEE encourages scholarly discourse on the latest
applications, tools, and methodologies being implemented in the field for the design
and development of computer and electrical systems.
Coverage
• Applied Electromagnetics
IGI Global is currently accepting
• Digital Electronics
manuscripts for publication within this
• Computer Architecture series. To submit a proposal for a volume in
• Programming this series, please contact our Acquisition
• Microprocessor Design Editors at [email protected] or
• Computer Science visit: http://www.igi-global.com/publish/.
• Sensor Technologies
• Analog Electronics
• Circuit Analysis
• VLSI Design
The Advances in Computer and Electrical Engineering (ACEE) Book Series (ISSN 2327-039X) is published by IGI
Global, 701 E. Chocolate Avenue, Hershey, PA 17033-1240, USA, www.igi-global.com. This series is composed of titles
available for purchase individually; each title is edited to be contextually exclusive from any other title within the series.
For pricing and ordering information please visit http://www.igi-global.com/book-series/advances-computer-electrical-
engineering/73675. Postmaster: Send all address changes to above address. Copyright © 2020 IGI Global. All rights,
including translation in other languages reserved by the publisher. No part of this series may be reproduced or used in any
form or by any means – graphics, electronic, or mechanical, including photocopying, recording, taping, or information and
retrieval systems – without written permission from the publisher, except for non commercial, educational use, including
classroom teaching purposes. The views expressed in this series are those of the authors, but not necessarily of IGI Global.
Titles in this Series
For a list of additional titles in this series, please visit:
https://www.igi-global.com/book-series/advances-computer-electrical-engineering/73675
Electrical Insulation Breakdown and Its Theory, Process, and Prevention Emerging
Research and Opportunities
Boxue Du (Tianjin University, China)
Engineering Science Reference • copyright 2020 • 230pp • H/C (ISBN: 9781522588856)
• US $215.00 (our price)
Challenges and Applications for Implementing Machine Learning in Computer Vision
Ramgopal Kashyap (Amity University Chhattisgarh, India) and A.V. Senthil Kumar
(Hindusthan College of Arts and Science, India)
Engineering Science Reference • copyright 2020 • 300pp • H/C (ISBN: 9781799801825)
• US $195.00 (our price)
Handbook of Research on Recent Developments in Electrical and Mechanical Engineering
Jamal Zbitou (University of Hassan 1st, Morocco) Catalin Iulian Pruncu (Imperial College
London, UK) and Ahmed Errkik (University of Hassan 1st, Morocco)
Engineering Science Reference • copyright 2020 • 553pp • H/C (ISBN: 9781799801177)
• US $255.00 (our price)
Architecture and Security Issues in Fog Computing Applications
Sam Goundar (The University of the South Pacific, Fiji) S. Bharath Bhushan (Sree
Vidyanikethan Engineering College, India) and Praveen Kumar Rayani (National Institute
of Technology, Durgapur, India)
Engineering Science Reference • copyright 2020 • 205pp • H/C (ISBN: 9781799801948)
• US $215.00 (our price)
Handbook of Research on Advanced Applications of Graph Theory in Modern Society
Madhumangal Pal (Vidyasagar University, India) Sovan Samanta (Tamralipta Mahavidyalaya,
India) and Anita Pal (National Institute of Technology Durgapur, India)
Engineering Science Reference • copyright 2020 • 591pp • H/C (ISBN: 9781522593805)
• US $245.00 (our price)
For an entire list of titles in this series, please visit:
https://www.igi-global.com/book-series/advances-computer-electrical-engineering/73675
701 East Chocolate Avenue, Hershey, PA 17033, USA
Tel: [phone] x100 • Fax: [phone]
E-Mail: [email protected] • www.igi-global.com
Table of Contents
Foreword.............................................................................................................xiv
Preface..................................................................................................................xv
Acknowledgment..............................................................................................xxiii
Chapter 1
Deep.Learning.Network:.Deep.Neural.Networks...................................................1
Bhanu Chander, Pondicherry University, India
Chapter 2
A.Journey.From.Neural.Networks.to.Deep.Networks:.Comprehensive.
Understanding.for.Deep.Learning.........................................................................31
Priyanka P. Patel, Chandubhai S. Patel Institute of Technology,
CHARUSAT University, India
Amit R. Thakkar, Chandubhai S. Patel Institute of Technology,
CHARUSAT University, India
Chapter 3
Current.Trends.in.Deep.Learning.Frameworks.With.Opportunities.and.Future.
Prospectus.............................................................................................................63
Chitra A. Dhawale, P. R. Pote College of Engineering and Management,
India
Krtika Dhawale, Indian Institute of Information Technology, Nagpur,
India
Chapter 4
Emotion.Recognition.From.Speech.Using.Perceptual.Filter.and.Neural.
Network.................................................................................................................78
Revathi A., SASTRA University, India
Sasikaladevi N., SASTRA University, India

Chapter 5
Ontology.Creation.................................................................................................92
Anjali Daisy, SASTRA University, India
Chapter 6
Semantic.Similarity.Using.Register.Linear.Question.Classification.(RLQC).
for.Question.Classification..................................................................................104
Shanthi Palaniappan, Sri Krishna College of Engineering and
Technology, India
Sridevi U. K., PSG College of Technology, India
Pathur Nisha S., Nehru Institute of Technology, India
Chapter 7
Knowledge.Graph.Generation.............................................................................115
Anjali Daisy, SASTRA University, India
Chapter 8
Develop.a.Neural.Model.to.Score.Bigram.of.Words.Using.Bag-of-Words.
Model.for.Sentiment.Analysis............................................................................122
Anumeera Balamurali, St.Joseph’s College of Engineering, India
Balamurali Ananthanarayanan, Tamilnadu Agriculture Department,
India
Chapter 9
Deep.Learning.Approach.for.Extracting.Catch.Phrases.from.Legal.
Documents..........................................................................................................143
Kayalvizhi S., SSN College of Engineering, India
Thenmozhi D., SSN College of Engineering, India
Chapter 10
Enhanced.Sentiment.Classification.Using.Recurrent.Neural.Networks.............159
Arunmozhi Mourougappane, St.Joseph’s College of Engineering, India
Suresh Jaganathan, SSN College of Engineering, India
Chapter 11
Natural.Language.Processing-Based.Information.Extraction.and.Abstraction.
for.Lease.Documents..........................................................................................170
Sumathi S., St.Joseph’s College of Engineering, India
Rajkumar S., HCL Technologies Ltd., India
Indumathi S., Jerusalem College of Engineering, India

Chapter 12
Neural.Network.Applications.in.Hate.Speech.Detection....................................188
Brian Tuan Khieu, San Jose State University, USA
Melody Moh, San Jose State University, USA
Compilation of References...............................................................................205
About the Contributors....................................................................................220
Index...................................................................................................................226
Detailed Table of Contents
Foreword.............................................................................................................xiv
Preface..................................................................................................................xv
Acknowledgment..............................................................................................xxiii
Chapter 1
Deep.Learning.Network:.Deep.Neural.Networks...................................................1
Bhanu Chander, Pondicherry University, India
Artificial.intelligence.(AI).is.defined.as.a.machine.that.can.do.everything.a.human.
being.can.do.and.produce.better.results..Means.AI.enlightening.that.data.can.
produce.a.solution.for.its.own.results..Inside.the.AI.ellipsoidal,.Machine.learning.
(ML).has.a.wide.variety.of.algorithms.produce.more.accurate.results..As.a.result.
of.technology,.improvement.increasing.amounts.of.data.are.available..But.with.ML.
and.AI,.it.is.very.difficult.to.extract.such.high-level,.abstract.features.from.raw.data,.
moreover.hard.to.know.what.feature.should.be.extracted..Finally,.we.now.have.deep.
learning;.these.algorithms.are.modeled.based.on.how.human.brains.process.the.data..
Deep.learning.is.a.particular.kind.of.machine.learning.that.provides.flexibility.and.
great.power,.with.its.attempts.to.learn.in.multiple.levels.of.representation.with.the.
operations.of.multiple.layers..Deep.learning.brief.overview,.platforms,.Models,.
Autoencoders,.CNN,.RNN,.and.Appliances.are.described.appropriately..Deep.
learning.will.have.many.more.successes.in.the.near.future.because.it.requires.very.
little.engineering.by.hand.
Chapter 2
A.Journey.From.Neural.Networks.to.Deep.Networks:.Comprehensive.
Understanding.for.Deep.Learning.........................................................................31
Priyanka P. Patel, Chandubhai S. Patel Institute of Technology,
CHARUSAT University, India
Amit R. Thakkar, Chandubhai S. Patel Institute of Technology,
CHARUSAT University, India

The.chapter.is.about.deep.learning.fundaments.and.its.recent.trends..The.chapter.
mentions.many.advanced.applications.and.deep.learning.models.and.networks.to.
easily.solve.those.applications.in.a.very.smart.way..Discussion.of.some.techniques.for.
computer.vision.problem.and.how.to.solve.with.deep.learning.approach.are.included..
After.taking.fundamental.knowledge.of.the.background.theory,.one.can.create.or.solve.
applications..The.current.state-of-the-art.of.deep.learning.for.education,.healthcare,.
agriculture,.industrial,.organizations,.and.research.and.development.applications.
are.very.fast.growing..The.chapter.is.about.types.of.learning.in.a.deep.learning.
approach,.what.kind.of.data.set.one.can.be.required,.and.what.kind.of.hardware.
facility.is.required.for.the.particular.complex.problem..For.unsupervised.learning.
problems,.Deep.learning.algorithms.have.been.designed,.but.in.the.same.way.Deep.
learning.is.also.solving.the.supervised.learning.problems.for.a.wide.variety.of.tasks.
Chapter 3
Current.Trends.in.Deep.Learning.Frameworks.With.Opportunities.and.Future.
Prospectus.............................................................................................................63
Chitra A. Dhawale, P. R. Pote College of Engineering and Management,
India
Krtika Dhawale, Indian Institute of Information Technology, Nagpur,
India
Artificial.Intelligence.(AI).is.going.through.its.golden.era.by.playing.an.important.
role.in.various.real-time.applications..Most.AI.applications.are.using.Machine.
learning.and.it.represents.the.most.promising.path.to.strong.AI..On.the.other.hand,.
Deep.Learning.(DL),.which.is.itself.a.kind.of.Machine.Learning.(ML),.is.becoming.
more.and.more.popular.and.successful.at.different.use.cases,.and.is.at.the.peak.
of.developments..Hence,.DL.is.becoming.a.leader.in.this.domain..To.foster.the.
growth.of.the.DL.community.to.a.greater.extent,.many.open.source.frameworks.
are.available.which.implemented.DL.algorithms..Each.framework.is.based.on.an.
algorithm.with.specific.applications..This.chapter.provides.a.brief.qualitative.review.
of.the.most.popular.and.comprehensive.DL.frameworks,.and.informs.end.users.of.
trends.in.DL.Frameworks..This.helps.them.make.an.informed.decision.to.choose.
the.best.DL.framework.that.suits.their.needs,.resources,.and.applications.so.they.
choose.a.proper.career.
Chapter 4
Emotion.Recognition.From.Speech.Using.Perceptual.Filter.and.Neural.
Network.................................................................................................................78
Revathi A., SASTRA University, India
Sasikaladevi N., SASTRA University, India
This.chapter.on.multi.speaker.independent.emotion.recognition.encompasses.the.use.
of.perceptual.features.with.filters.spaced.in.Equivalent.rectangular.bandwidth.(ERB).