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Title
Data visualization and knowledge engineering : spotting data points with artificial intelligence / Jude Hemanth, Madhulika Bhatia, Oana Geman, editors.
ISBN
9783030257972 (electronic book)
3030257975 (electronic book)
9783030257965
Publication Details
Cham : Springer, ©2020.
Language
English
Description
1 online resource (321 pages)
Item Number
10.1007/978-3-030-25
Call Number
QA76.9.I52
Dewey Decimal Classification
001.4/226
Summary
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, d esigning and using KBSs in cyberspace; Semantic Web.
Access Note
Access limited to authorized users.
Source of Description
Description based on print version record.
Series
Lecture Notes on Data Engineering and Communications Technologies ; v. 32.
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