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Recommender Systems Beyond E-Commerce: Presence and Future

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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.

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© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2021

Authors and Affiliations

  1. 1.Institute of Software Technology, Applied Artificial Intelligence, TU GrazGrazAustria

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