Skip to main content

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1101))

  • 62 Accesses

Abstract

In the modern world, easy and rapid access to up-to-date data and information that is relevant to specific tasks and studies is crucial. Knowledge can be acquired through recommendation systems, which enable opportunities to gain competitive advantages, as well as assisting in the management of financial resources, available goods, and scientific research more effectively. Knowledge relies heavily on properly structured information; this derives from source data.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
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

Purchases are for personal use only

Institutional subscriptions

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Jarosław Protasiewicz .

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Protasiewicz, J. (2023). Conclusions. In: Knowledge Recommendation Systems with Machine Intelligence Algorithms. Studies in Computational Intelligence, vol 1101. Springer, Cham. https://doi.org/10.1007/978-3-031-32696-7_7

Download citation

Publish with us

Policies and ethics