Skip to main content
SpringerLink
Log in

Data Visualization and Knowledge Engineering

Spotting Data Points with Artificial Intelligence

  • Book
  • © 2020

Overview

Editors:
  1. Jude Hemanth

    1. Department of Electronics and Communication Engineering (ECE), Karunya University, Coimbatore, India

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  2. Madhulika Bhatia

    1. Amity University, Noida, India

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  3. Oana Geman

    1. Department of Electrical Engineering and Computer Science, Ştefan cel Mare University of Suceava, Suceava, Romania

    View editor publications

    You can also search for this editor in PubMed   Google Scholar

  • Includes recent research on data visualization and knowledge engineering
  • Presents basic research on visual data exploration as well as a number of visualization techniques
  • Written by experts in the field

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies (LNDECT, volume 32)

This is a preview of subscription content, log in via an institution to check access.

Access this book

Log in via an institution
eBook USD 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

Licence this eBook for your library

Institutional subscriptions

Table of contents (13 chapters)

  1. Front Matter

    Pages i-vi
    Download chapter PDF

  2. Cross Projects Defect Prediction Modeling

    • Lipika Goel, Sonam Gupta
    Pages 1-21

  3. Recommendation Systems for Interactive Multimedia Entertainment

    • Shilpi Aggarwal, Dipanjan Goswami, Madhurima Hooda, Amirta Chakravarty, Arpan Kar, Vasudha
    Pages 23-48

  4. Image Collection Summarization: Past, Present and Future

    • Anurag Singh, Deepak Kumar Sharma
    Pages 49-78

  5. Deep Learning Based Semantic Segmentation Applied to Satellite Image

    • Manami Barthakur, Kandarpa Kumar Sarma
    Pages 79-107

  6. A Deep Dive into Supervised Extractive and Abstractive Summarization from Text

    • Monalisa Dey, Dipankar Das
    Pages 109-132

  7. Semantic Web and Data Visualization

    • Abhinav Singh, Utsha Sinha, Deepak Kumar Sharma
    Pages 133-150

  8. Challenges and Responses Towards Sustainable Future Through Machine Learning and Deep Learning

    • Saksham Gulati, Shilpi Sharma
    Pages 151-169

  9. Brain Tumor Segmentation Using OTSU Embedded Adaptive Particle Swarm Optimization Method and Convolutional Neural Network

    • Surbhi Vijh, Shilpi Sharma, Prashant Gaurav
    Pages 171-194

  10. Analysis and Visualization of User Navigations on Web

    • Honey Jindal, Neetu Sardana, Raghav Mehta
    Pages 195-221

  11. Research Trends for Named Entity Recognition in Hindi Language

    • Arti Jain, Devendra K. Tayal, Divakar Yadav, Anuja Arora
    Pages 223-248

  12. Data Visualization Techniques, Model and Taxonomy

    • Shreyans Pathak, Shashwat Pathak
    Pages 249-271

  13. Prevalence of Visualization Techniques in Data Mining

    • Rosy Madaan, Komal Kumar Bhatia
    Pages 273-298

  14. Relevant Subsection Retrieval for Law Domain Question Answer System

    • Aayushi Verma, Jorge Morato, Arti Jain, Anuja Arora
    Pages 299-319
Back to top

Keywords

About this book

This book presents the fundamentals and advances in the field of data visualization and knowledge engineering, supported by case studies and practical examples. Data visualization and engineering has been instrumental in the development of many data-driven products and processes. As such the book promotes basic research on data visualization and knowledge engineering toward data engineering and knowledge.
Visual data exploration focuses on perception of information and manipulation of data to enable even non-expert users to extract knowledge. A number of visualization techniques are used in a variety of systems that provide users with innovative ways to interact with data and reveal patterns. A variety of scalable data visualization techniques are required to deal with constantly increasing volume of data in different formats.
Knowledge engineering deals with the simulation of the exchange of ideas and the development of smart information systems in which reasoning and knowledge play an important role.
Presenting research in areas like data visualization and knowledge engineering, this book is a valuable resource for students, scholars and researchers in the field.
Each chapter is self-contained and offers an in-depth analysis of real-world applications. It discusses topics including (but not limited to) spatial data visualization; biomedical visualization and applications; image/video summarization and visualization; perception and cognition in visualization; visualization taxonomies and models; abstract data visualization; information and graph visualization; knowledge engineering; human–machine cooperation; metamodeling; natural language processing; architectures of database, expert and knowledge-based systems; knowledge acquisition methods; applications, case studies and management issues: data administration issues and knowledge; tools for specifying and developing data and knowledge bases using tools based on communication aspects involved in implementing, designing and using KBSs in cyberspace; Semantic Web.

Editors and Affiliations

  • Department of Electronics and Communication Engineering (ECE), Karunya University, Coimbatore, India

    Jude Hemanth

  • Amity University, Noida, India

    Madhulika Bhatia

  • Department of Electrical Engineering and Computer Science, Ştefan cel Mare University of Suceava, Suceava, Romania

    Oana Geman

Bibliographic Information

Publish with us

Policies and ethics

Back to top

Search

Navigation