رکورد قبلیرکورد بعدی

" Realtime data mining : "


Document Type : BL
Record Number : 603904
Doc. No : b433123
Main Entry : Paprotny, Alexander
Title & Author : Realtime data mining : : toward the self-learning recommendation engine /\ Alexander Paprotny, Michael Thess
Series Statement : Applied and numerical harmonic analysis
Page. NO : 1 online resource
ISBN : 3319013211 (electronic bk.)
: : 9783319013213 (electronic bk.)
: 9783319013206
Bibliographies/Indexes : Includes bibliographical references
Abstract : Describing novel mathematical concepts for recommendation engines, Realtime Data Mining: Self-Learning Techniques for Recommendation Enginesfeatures 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. Thismonograph appeals to computer scientists and specialists in machine learning, especially from the area of recommender systems, because it conveys a new way of realtime thinkingby 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
Subject : Data mining
Dewey Classification : ‭006.3/12‬
LC Classification : ‭QA76.9.D343‬
Added Entry : Thess, Michael
Added Entry : Ohio Library and Information Network
کپی لینک

پیشنهاد خرید
پیوستها
Search result is zero
نظرسنجی
نظرسنجی منابع دیجیتال

1 - آیا از کیفیت منابع دیجیتال راضی هستید؟