Realtime Data Mining - Self-Learning Techniques for Recommendation Engines (Hardcover, 1st ed. 2013, Corr. 2nd printing 2014)

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, it presents promising results of numerous experiments on real-world data. The area of realtime data mining is currently developing at an exceptionally dynamic pace, and realtime data mining systems are the counterpart of today's "classic" data mining systems. Whereas the latter learn from historical data and then use it to deduce necessary actions, realtime analytics systems learn and act continuously and autonomously. In the vanguard of these new analytics systems are recommendation engines. They are principally found on the Internet, where all information is available in realtime and an immediate feedback is guaranteed. This monograph appeals to computer scientists and specialists in machine learning, especially from the area of recommender systems, because it conveys a new way of realtime thinking by considering recommendation tasks as control-theoretic problems. Realtime Data Mining: Self-Learning Techniques for Recommendation Engines will also interest application-oriented mathematicians because it consistently combines some of the most promising mathematical areas, namely control theory, multilevel approximation, and tensor factorization.

General

Imprint:	Birkhauser Verlag AG
Country of origin:	Switzerland
Series:	Applied and Numerical Harmonic Analysis
Release date:	April 2014
First published:	2013
Authors:	Alexander Paprotny • Michael Thess
Dimensions:	235 x 155 x 24mm (L x W x T)
Format:	Hardcover
Pages:	313
Edition:	1st ed. 2013, Corr. 2nd printing 2014
ISBN-13:	978-3-319-01320-6
Categories:	Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematical modelling Books > Computing & IT > Computer software packages > Other software packages > Mathematical & statistical software Books > Computing & IT > Applications of computing > Databases > Data mining Promotions
LSN:	3-319-01320-3
Barcode:	9783319013206

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