Electronic Resource

Realtime data mining

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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.

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

E722

Penerbit

Swiss : Birkhäuser Cham., 2013

Deskripsi Fisik

xxiii, 313 hlm.

Bahasa

English

ISBN/ISSN

9783319013213

Klasifikasi

NONE

Tipe Isi

text

Tipe Media

computer

Tipe Pembawa

online resource

Edisi

Ed.1

Subjek

Sains dan Rekayasa Komputasi

Info Detail Spesifik

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Pernyataan Tanggungjawab

Alexander Paprotny, Michael Thess

Versi lain/terkait

Lampiran Berkas

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