Skip to main content
Book cover

Modeling Fuzzy Spatiotemporal Data with XML

  • Book
  • © 2020

Overview

  • Highlights the latest advances in fuzzy spatiotemporal XML data management
  • Focuses on technologies and approaches to Web-based spatiotemporal data management with uncertainty
  • Covers fuzzy spatiotemporal data models, consistencies, queries, construction and storage, and semantic modeling
  • Offers an essential guide for researchers, practitioners, and graduate students alike

Part of the book series: Studies in Computational Intelligence (SCI, volume 894)

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

Access this book

eBook USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 169.99
Price excludes VAT (USA)
  • Durable hardcover 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 (8 chapters)

Keywords

About this book

This book offers in-depth insights into the rapidly growing topic of technologies and approaches to modeling fuzzy spatiotemporal data with XML. The topics covered include representation of fuzzy spatiotemporal XML data, topological relationship determination for fuzzy spatiotemporal XML data, mapping between the fuzzy spatiotemporal relational database model and fuzzy spatiotemporal XML data model, and consistencies in fuzzy spatiotemporal XML data updating. Offering a comprehensive guide to the latest research on fuzzy spatiotemporal XML data management, the book is intended to provide state-of-the-art information for researchers, practitioners, and graduate students of Web intelligence, as well as data and knowledge engineering professionals confronted with non-traditional applications that make the use of conventional approaches difficult or impossible. 

Authors and Affiliations

  • College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China

    Zongmin Ma, Li Yan

  • College of Information Science and Engineering, Northeastern University (Qinhuangdao), Qinhuangdao, China

    Luyi Bai

Bibliographic Information

Publish with us