Recommendation Engines

Robert Ball and Brian Rague
Additional contact information
Robert Ball: Weber State University
Brian Rague: Weber State University

Chapter Chapter 7 in The Beginner's Guide to Data Science, 2022, pp 143-153 from Springer

Abstract: Abstract A recommendation engine is a set of algorithms designed to predict (or recommend) a particular product, service, or other item of interest a user or customer wishes to buy or utilize in some manner. The various choices in recommender systems are detailed with an example that analyzes demographic information for the purposes of promoting products to consumers.

Date: 2022
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-031-07865-1_7

Ordering information: This item can be ordered from
http://www.springer.com/9783031078651

DOI: 10.1007/978-3-031-07865-1_7

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().