Recommender Systems Beyond E-Commerce: Presence and Future

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Recommender systems are supporting users in the identification of items that fulfill their wishes and needs and are also helping to foster consumer happiness. These systems have been successfully applied in different application domains—examples thereof are the recommendation of movies, books, digital cameras, points of interest, financial services, and software requirements. The major objectives of this chapter are to provide an overview of recommendation approaches including criteria when to use which algorithm, to show different applications of recommendation algorithms going beyond standard e-commerce scenarios and to discuss issues for future research
Original languageEnglish
Title of host publicationConsumer Happiness: Multiple Perspectives
PublisherSpringer Singapore
Pages203-230
Number of pages28
Edition1
ISBN (Electronic)978-981-336-374-8
ISBN (Print)978-981-336-373-1
DOIs
Publication statusPublished - 2021

Publication series

NameStudies in Rhythm Engineering
PublisherSpringer Nature

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