Realtime Data Mining (Record no. 96534)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 04176nam a22004935i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-3-319-01321-3 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | DE-He213 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20140220082840.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
| fixed length control field | cr nn 008mamaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 131203s2013 gw | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9783319013213 |
| -- | 978-3-319-01321-3 |
| 024 7# - OTHER STANDARD IDENTIFIER | |
| Standard number or code | 10.1007/978-3-319-01321-3 |
| Source of number or code | doi |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | QA71-90 |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | PDE |
| Source | bicssc |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | COM014000 |
| Source | bisacsh |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | MAT003000 |
| Source | bisacsh |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 004 |
| Edition number | 23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Paprotny, Alexander. |
| Relator term | author. |
| 245 10 - TITLE STATEMENT | |
| Title | Realtime Data Mining |
| Medium | [electronic resource] : |
| Remainder of title | Self-Learning Techniques for Recommendation Engines / |
| Statement of responsibility, etc | by Alexander Paprotny, Michael Thess. |
| 264 #1 - | |
| -- | Cham : |
| -- | Springer International Publishing : |
| -- | Imprint: Birkhäuser, |
| -- | 2013. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | XXIII, 313 p. 100 illus., 12 illus. in color. |
| Other physical details | online resource. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | cr |
| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
| -- | |
| -- | rda |
| 490 1# - SERIES STATEMENT | |
| Series statement | Applied and Numerical Harmonic Analysis, |
| International Standard Serial Number | 2296-5009 |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | 1 Brave New Realtime World – Introduction -- 2 Strange Recommendations? – On The Weaknesses Of Current Recommendation Engines -- 3 Changing Not Just Analyzing – Control Theory And Reinforcement Learning -- 4 Recommendations As A Game – Reinforcement Learning For Recommendation Engines -- 5 How Engines Learn To Generate Recommendations – Adaptive Learning Algorithms -- 6 Up The Down Staircase – Hierarchical Reinforcement Learning -- 7 Breaking Dimensions – Adaptive Scoring With Sparse Grids -- 8 Decomposition In Transition - Adaptive Matrix Factorization -- 9 Decomposition In Transition Ii - Adaptive Tensor Factorization -- 10 The Big Picture – Towards A Synthesis Of Rl And Adaptive Tensor Factorization -- 11 What Cannot Be Measured Cannot Be Controlled - Gauging Success With A/B Tests -- 12 Building A Recommendation Engine – The Xelopes Library -- 13 Last Words – Conclusion -- References -- Summary Of Notation. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | 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. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Mathematics. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computer science. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computer software. |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Mathematics. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computational Science and Engineering. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Mathematical Applications in Computer Science. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Mathematical Software. |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Thess, Michael. |
| Relator term | author. |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | SpringerLink (Online service) |
| 773 0# - HOST ITEM ENTRY | |
| Title | Springer eBooks |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Display text | Printed edition: |
| International Standard Book Number | 9783319013206 |
| 830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
| Uniform title | Applied and Numerical Harmonic Analysis, |
| -- | 2296-5009 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | http://dx.doi.org/10.1007/978-3-319-01321-3 |
| 912 ## - | |
| -- | ZDB-2-SMA |
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