Realtime data mining : self-learning techniques for recommendation engines /
Describing novel mathematical concepts for recommendation engines, Realtime Data Mining: Self-Learning Techniques for Recommendation Engines features a sound mathematical framework unifying approaches based on control and learning theories, tensor factorization, and hierarchical methods. Furthermore...
Saved in:
Main Authors: | Paprotny, Alexander (Author), Thess, Michael (Author) |
---|---|
Corporate Author: | SpringerLink (Online service) |
Format: | eBook |
Language: | English |
Published: |
Cham
Springer International Publishing Imprint: Birkhäuser,
2013.
|
Series: | Applied and Numerical Harmonic Analysis,
|
Subjects: | |
Online Access: | Click here to view the full text content |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Realtime web apps : with HTML5 WebSocket, PHP, and jQuery /
by: Lengstorf, Jason, et al.
Published: (2013) -
Embedded realtime systems programming /
by: Iyer, Sriram V. -
Embedded realtime systems programming
by: Iyer, Sriram V.
Published: (2004) -
Embedded realtime systems programming
by: Iyer, Sriram V.
Published: (2004) -
Mathematical tools for data mining : set theory, partial orders, combinatorics /
by: Simovici, Dan A., et al.
Published: (2014)