Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.
Recommendation systems: Principles, methods and evaluation
1.282
Zitationen
3
Autoren
2015
Jahr
Abstract
On the Internet, where the number of choices is overwhelming, there is need to filter, prioritize and efficiently deliver relevant information in order to alleviate the problem of information overload, which has created a potential problem to many Internet users. Recommender systems solve this problem by searching through large volume of dynamically generated information to provide users with personalized content and services. This paper explores the different characteristics and potentials of different prediction techniques in recommendation systems in order to serve as a compass for research and practice in the field of recommendation systems.
Ähnliche Arbeiten
Matrix Factorization Techniques for Recommender Systems
2009 · 11.449 Zit.
Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions
2005 · 10.142 Zit.
Item-based collaborative filtering recommendation algorithms
2001 · 8.933 Zit.
Neural Collaborative Filtering
2017 · 6.432 Zit.
Evaluating collaborative filtering recommender systems
2004 · 5.719 Zit.