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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.
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.
Specifically addresses recommendation engines from a mathematically rigorous viewpoint
Discusses a control-theoretic framework for recommendation engines
Provides applications to a number of areas within engineering and computer science
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.
Erscheinungsjahr: | 2016 |
---|---|
Fachbereich: | EDV |
Genre: | Informatik |
Rubrik: | Naturwissenschaften & Technik |
Thema: | Lexika |
Medium: | Taschenbuch |
Seiten: | 340 |
Reihe: | Applied and Numerical Harmonic Analysis |
Inhalt: |
xxiii
313 S. 12 s/w Illustr. 88 farbige Illustr. 313 p. 100 illus. 88 illus. in color. |
ISBN-13: | 9783319344454 |
ISBN-10: | 3319344455 |
Sprache: | Englisch |
Ausstattung / Beilage: | Paperback |
Einband: | Kartoniert / Broschiert |
Autor: |
Thess, Michael
Paprotny, Alexander |
Auflage: | Softcover reprint of the original 1st ed. 2013 |
Hersteller: |
Springer International Publishing
Applied and Numerical Harmonic Analysis |
Maße: | 235 x 155 x 19 mm |
Von/Mit: | Michael Thess (u. a.) |
Erscheinungsdatum: | 27.08.2016 |
Gewicht: | 0,517 kg |
Specifically addresses recommendation engines from a mathematically rigorous viewpoint
Discusses a control-theoretic framework for recommendation engines
Provides applications to a number of areas within engineering and computer science
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.
Erscheinungsjahr: | 2016 |
---|---|
Fachbereich: | EDV |
Genre: | Informatik |
Rubrik: | Naturwissenschaften & Technik |
Thema: | Lexika |
Medium: | Taschenbuch |
Seiten: | 340 |
Reihe: | Applied and Numerical Harmonic Analysis |
Inhalt: |
xxiii
313 S. 12 s/w Illustr. 88 farbige Illustr. 313 p. 100 illus. 88 illus. in color. |
ISBN-13: | 9783319344454 |
ISBN-10: | 3319344455 |
Sprache: | Englisch |
Ausstattung / Beilage: | Paperback |
Einband: | Kartoniert / Broschiert |
Autor: |
Thess, Michael
Paprotny, Alexander |
Auflage: | Softcover reprint of the original 1st ed. 2013 |
Hersteller: |
Springer International Publishing
Applied and Numerical Harmonic Analysis |
Maße: | 235 x 155 x 19 mm |
Von/Mit: | Michael Thess (u. a.) |
Erscheinungsdatum: | 27.08.2016 |
Gewicht: | 0,517 kg |