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Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges

  • Book
  • © 2021

Overview

Editors:
  1. Aboul Ella Hassanien

    1. Faculty of Computer and Artificial Intelligence, Cairo University, Giza, Egypt

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    You can also search for this editor in PubMed   Google Scholar

  2. Ashraf Darwish

    1. Faculty of Science, Helwan University, Helwan, Egypt

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  • Presents recent research in Machine Learning and Big Data Analytics
  • Provides an Analysis, Applications, and Challenges of Big Data and Machine Learning
  • Exhibits various technologies to create systems that can learn from the data in their environment and then make predictions and take actions when confronted with a new situation

Part of the book series: Studies in Big Data (SBD, volume 77)

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Table of contents (30 chapters)

  1. Front Matter

    Pages i-xi
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  2. Artificial Intelligence and Data Mining Applications

    1. Front Matter

      Pages 1-1
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    2. Rough Sets and Rule Induction from Indiscernibility Relations Based on Possible World Semantics in Incomplete Information Systems with Continuous Domains

      • Michinori Nakata, Hiroshi Sakai, Keitarou Hara
      Pages 3-23

    3. Big Data Analytics and Preprocessing

      • Noha Shehab, Mahmoud Badawy, Hesham Arafat
      Pages 25-43

    4. Artificial Intelligence-Based Plant Diseases Classification

      • Lobna M. Abou El-Maged, Ashraf Darwish, Aboul Ella Hassanien
      Pages 45-61

    5. Artificial Intelligence in Potato Leaf Disease Classification: A Deep Learning Approach

      • Nour Eldeen M. Khalifa, Mohamed Hamed N. Taha, Lobna M. Abou El-Maged, Aboul Ella Hassanien
      Pages 63-79

    6. Granules-Based Rough Set Theory for Circuit Breaker Fault Diagnosis

      • Rizk M. Rizk-Allah, Aboul Ella Hassanien
      Pages 81-92

    7. SQL Injection Attacks Detection and Prevention Based on Neuro—Fuzzy Technique

      • Doaa E. Nofal, Abeer A. Amer
      Pages 93-112

    8. Convolutional Neural Network with Batch Normalization for Classification of Endoscopic Gastrointestinal Diseases

      • Dalia Ezzat, Heba M. Afify, Mohamed Hamed N. Taha, Aboul Ella Hassanien
      Pages 113-128

    9. A Chaotic Search-Enhanced Genetic Algorithm for Bilevel Programming Problems

      • Y. Abo-Elnaga, S. Nasr, I. El-Desoky, Z. Hendawy, A. Mousa
      Pages 129-146

    10. Bio-inspired Machine Learning Mechanism for Detecting Malicious URL Through Passive DNS in Big Data Platform

      • Saad M. Darwish, Ali E. Anber, Saleh Mesbah
      Pages 147-161

  3. Machine Learning and Applications

    1. Front Matter

      Pages 163-163
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    2. TargetAnalytica: A Text Analytics Framework for Ranking Therapeutic Molecules in the Bibliome

      • Ahmed Abdeen Hamed, Agata Leszczynska, Megean Schoenberg, Gergely Temesi, Karin Verspoor
      Pages 165-184

    3. Earthquakes and Thermal Anomalies in a Remote Sensing Perspective

      • Utpal Kanti Mukhopadhyay, Richa N. K. Sharma, Shamama Anwar, Atma Deep Dutta
      Pages 185-217

    4. Literature Review with Study and Analysis of the Quality Challenges of Recommendation Techniques and Their Application in Movie Ratings

      • Hagar El Fiky, Wedad Hussein, Rania El Gohary
      Pages 219-241

    5. Predicting Student Retention Among a Homogeneous Population Using Data Mining

      • Ghazala Bilquise, Sherief Abdallah, Thaeer Kobbaey
      Pages 243-260

    6. An Approach for Textual Based Clustering Using Word Embedding

      • Ehab Terra, Ammar Mohammed, Hesham Hefny
      Pages 261-280

    7. A Survey on Speckle Noise Reduction for SAR Images

      • Ahmed S. Mashaly, Tarek A. Mahmoud
      Pages 281-302

    8. Comparative Analysis of Different Approaches to Human Activity Recognition Based on Accelerometer Signals

      • Walid Gomaa
      Pages 303-322

  4. Deep Learning Technology for Big Data Analytics

    1. Front Matter

      Pages 323-323
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Keywords

About this book

This book is intended to present the state of the art in research on machine learning and big data analytics. The accepted chapters covered many themes including  artificial intelligence and data mining applications, machine learning and applications, deep learning technology for big data analytics, and modeling, simulation, and security with big data. It is a valuable resource for researchers in the area of big data analytics and its applications.


Editors and Affiliations

  • Faculty of Computer and Artificial Intelligence, Cairo University, Giza, Egypt

    Aboul Ella Hassanien

  • Faculty of Science, Helwan University, Helwan, Egypt

    Ashraf Darwish

Bibliographic Information

  • Book Title: Machine Learning and Big Data Analytics Paradigms: Analysis, Applications and Challenges

  • Editors: Aboul Ella Hassanien, Ashraf Darwish

  • Series Title: Studies in Big Data

  • DOI: https://doi.org/10.1007/978-3-030-59338-4

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021

  • Hardcover ISBN: 978-3-030-59337-7Published: 15 December 2020

  • Softcover ISBN: 978-3-030-59340-7Published: 16 December 2021

  • eBook ISBN: 978-3-030-59338-4Published: 14 December 2020

  • Series ISSN: 2197-6503

  • Series E-ISSN: 2197-6511

  • Edition Number: 1

  • Number of Pages: XI, 648

  • Number of Illustrations: 85 b/w illustrations, 182 illustrations in colour

  • Topics: Data Engineering, Computational Intelligence, Big Data, Machine Learning

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