Machine Learning Paradigms Applications in Recommender Systems /

This timely book presents Applications in Recommender Systems which are making recommendations using machine learning algorithms trained via examples of content the user likes or dislikes. Recommender systems built on the assumption of availability of both positive and negative examples do not perfo...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Lampropoulos, Aristomenis S. (Συγγραφέας), Tsihrintzis, George A. (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2015.
Σειρά:Intelligent Systems Reference Library, 92
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • Introduction
  • Review of Previous Work Related to Recommender Systems
  • The Learning Problem.-Content Description of Multimedia Data
  • Similarity Measures for Recommendations based on Objective Feature Subset Selection
  • Cascade Recommendation Methods
  • Evaluation of Cascade Recommendation Methods
  • Conclusions and Future Work.