Recommendation engines
"How does Netflix know just what to suggest you watch next? How does Amazon determine what a "customer like you" has also purchased? The answer is recommender systems, the technological concept that lies at the heart of most of the successful companies in the digital economy. Michael...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Schrage, Michael [verfasserIn] |
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| Format: |
E-Book |
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| Sprache: |
Englisch |
| Erschienen: |
Cambridge, Massachusetts: The MIT Press ; 2020 |
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| Rechteinformationen: |
Restricted to subscribers or individual electronic text purchasers. |
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| Schlagwörter: |
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| Anmerkung: |
Includes bibliographical references and index |
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| Umfang: |
1 PDF. |
| Beschreibung: |
Mode of access: World Wide Web. |
| Reihe: |
The MIT Press essential knowledge series |
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| Links: | |
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| ISBN: |
978-0-262-35879-8 0-262-35878-6 |
| Katalog-ID: |
1860731376 |
|---|
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| 520 | |a "How does Netflix know just what to suggest you watch next? How does Amazon determine what a "customer like you" has also purchased? The answer is recommender systems, the technological concept that lies at the heart of most of the successful companies in the digital economy. Michael Schrage starts with the origins of recommender systems, which go back further than you think (see: the Oracle at Delphi for one of history's earliest recommenders), and a history of the first companies to harness recommendations. He then discusses the technology behind how recommenders work: the AI and machine learning algorithms that power these recommender platforms. Next he discusses the role of user experience, and how recommender systems are designed, and how design choices function as nudges to make certain recommendations more salient than others. He explores three case studies: Spotify, Bytedance, and Stitch Fix, looking at how recommenders can create new business solutions and how algorithms can go beyond curation to content creation. The concluding chapter on the future of recommender systems is perhaps the most enlightening. Moving away from technology and business, Schrage embraces the philosophical, probing the role of free will in a world mediated by recommender systems (a recommendation inherently offers a choice; without the element of choice, any digital manipulation of our preferences cannot truly be called a "recommendation"), and exploring the role of recommender systems as a means of improving the self. In the vein of Free Will, this book presents the essential information while revealing the author's point of view. Schrage wants to push our understanding of recommender systems beyond the technological, to understand what societal role they play and what opportunities they offer now and in the future"-- | ||
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9780262358798 electronic bk. 978-0-262-35879-8 0262358786 0-262-35878-6 (DE-627)1860731376 (DE-599)KEP062309994 (OCoLC)1197707113 (MITPRESS)9198868 (EBP)062309994 DE-627 ger DE-627 rda eng 025.04 23 Schrage, Michael verfasserin aut Recommendation engines Michael Schrage Cambridge, Massachusetts The MIT Press 2020 1 PDF. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The MIT Press essential knowledge series Includes bibliographical references and index Restricted to subscribers or individual electronic text purchasers. "How does Netflix know just what to suggest you watch next? How does Amazon determine what a "customer like you" has also purchased? The answer is recommender systems, the technological concept that lies at the heart of most of the successful companies in the digital economy. Michael Schrage starts with the origins of recommender systems, which go back further than you think (see: the Oracle at Delphi for one of history's earliest recommenders), and a history of the first companies to harness recommendations. He then discusses the technology behind how recommenders work: the AI and machine learning algorithms that power these recommender platforms. Next he discusses the role of user experience, and how recommender systems are designed, and how design choices function as nudges to make certain recommendations more salient than others. He explores three case studies: Spotify, Bytedance, and Stitch Fix, looking at how recommenders can create new business solutions and how algorithms can go beyond curation to content creation. The concluding chapter on the future of recommender systems is perhaps the most enlightening. Moving away from technology and business, Schrage embraces the philosophical, probing the role of free will in a world mediated by recommender systems (a recommendation inherently offers a choice; without the element of choice, any digital manipulation of our preferences cannot truly be called a "recommendation"), and exploring the role of recommender systems as a means of improving the self. In the vein of Free Will, this book presents the essential information while revealing the author's point of view. Schrage wants to push our understanding of recommender systems beyond the technological, to understand what societal role they play and what opportunities they offer now and in the future"-- Mode of access: World Wide Web. Recommender systems (Information filtering) 9780262539074 Erscheint auch als Druck-Ausgabe 9780262539074 https://ieeexplore.ieee.org/book/9198868 X:MITPRESS Verlag lizenzpflichtig ZDB-37-IEM 2020 GBV_ILN_22 ISIL_DE-18 SYSFLAG_1 GBV_KXP GBV_ILN_22_i22818 GBV_ILN_23 ISIL_DE-830 GBV_ILN_62 ISIL_DE-28 GBV_ILN_100 ISIL_DE-Ma9 GBV_ILN_370 ISIL_DE-1373 BO 045F 025.04 22 01 0018 4391550474 olrm-h228-MITIEEE zi22818 17-10-23 23 01 0830 4391553562 olr-MIT i z 17-10-23 62 01 0028 4391568977 OLR-MIT Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. z 17-10-23 100 01 3100 4472471256 09 --%%-- eBook MIT Press --%%-- --%%-- OLR-MIT-CEC Vervielfältigungen (z.B. Kopien, Downloads) sind nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. z 30-01-24 370 01 4370 4391539012 olr-ebook mitieee Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 17-10-23 22 01 0018 Volltextzugang Campus https://ieeexplore.ieee.org/book/9198868 22 01 0018 Nur für Angehörige der Universität Hamburg: Volltextzugang von außerhalb des Campus http://emedien.sub.uni-hamburg.de/han/ieee/ieeexplore.ieee.org/book/9198868 23 01 0830 MIT Press EBook https://ieeexplore.ieee.org/book/9198868 62 01 0028 https://ieeexplore.ieee.org/book/9198868 100 01 3100 https://ieeexplore.ieee.org/book/9198868 100 01 3100 für Uniangehörige: Zugang weltweit http://han.med.uni-magdeburg.de/han/mitvia-ieee/ieeexplore.ieee.org/book/9198868 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://ieeexplore.ieee.org/book/9198868 23 01 0830 2018-01805, 2018-01806, 2018-01808 22 01 0018 olrm-h228-MITIEEE 23 01 0830 olr-MIT 62 01 0028 OLR-MIT 100 01 3100 OLR-MIT-CEC 370 01 4370 olr-ebook mitieee 370 01 4370 2021.12.01 |
| spelling |
9780262358798 electronic bk. 978-0-262-35879-8 0262358786 0-262-35878-6 (DE-627)1860731376 (DE-599)KEP062309994 (OCoLC)1197707113 (MITPRESS)9198868 (EBP)062309994 DE-627 ger DE-627 rda eng 025.04 23 Schrage, Michael verfasserin aut Recommendation engines Michael Schrage Cambridge, Massachusetts The MIT Press 2020 1 PDF. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The MIT Press essential knowledge series Includes bibliographical references and index Restricted to subscribers or individual electronic text purchasers. "How does Netflix know just what to suggest you watch next? How does Amazon determine what a "customer like you" has also purchased? The answer is recommender systems, the technological concept that lies at the heart of most of the successful companies in the digital economy. Michael Schrage starts with the origins of recommender systems, which go back further than you think (see: the Oracle at Delphi for one of history's earliest recommenders), and a history of the first companies to harness recommendations. He then discusses the technology behind how recommenders work: the AI and machine learning algorithms that power these recommender platforms. Next he discusses the role of user experience, and how recommender systems are designed, and how design choices function as nudges to make certain recommendations more salient than others. He explores three case studies: Spotify, Bytedance, and Stitch Fix, looking at how recommenders can create new business solutions and how algorithms can go beyond curation to content creation. The concluding chapter on the future of recommender systems is perhaps the most enlightening. Moving away from technology and business, Schrage embraces the philosophical, probing the role of free will in a world mediated by recommender systems (a recommendation inherently offers a choice; without the element of choice, any digital manipulation of our preferences cannot truly be called a "recommendation"), and exploring the role of recommender systems as a means of improving the self. In the vein of Free Will, this book presents the essential information while revealing the author's point of view. Schrage wants to push our understanding of recommender systems beyond the technological, to understand what societal role they play and what opportunities they offer now and in the future"-- Mode of access: World Wide Web. Recommender systems (Information filtering) 9780262539074 Erscheint auch als Druck-Ausgabe 9780262539074 https://ieeexplore.ieee.org/book/9198868 X:MITPRESS Verlag lizenzpflichtig ZDB-37-IEM 2020 GBV_ILN_22 ISIL_DE-18 SYSFLAG_1 GBV_KXP GBV_ILN_22_i22818 GBV_ILN_23 ISIL_DE-830 GBV_ILN_62 ISIL_DE-28 GBV_ILN_100 ISIL_DE-Ma9 GBV_ILN_370 ISIL_DE-1373 BO 045F 025.04 22 01 0018 4391550474 olrm-h228-MITIEEE zi22818 17-10-23 23 01 0830 4391553562 olr-MIT i z 17-10-23 62 01 0028 4391568977 OLR-MIT Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. z 17-10-23 100 01 3100 4472471256 09 --%%-- eBook MIT Press --%%-- --%%-- OLR-MIT-CEC Vervielfältigungen (z.B. Kopien, Downloads) sind nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. z 30-01-24 370 01 4370 4391539012 olr-ebook mitieee Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 17-10-23 22 01 0018 Volltextzugang Campus https://ieeexplore.ieee.org/book/9198868 22 01 0018 Nur für Angehörige der Universität Hamburg: Volltextzugang von außerhalb des Campus http://emedien.sub.uni-hamburg.de/han/ieee/ieeexplore.ieee.org/book/9198868 23 01 0830 MIT Press EBook https://ieeexplore.ieee.org/book/9198868 62 01 0028 https://ieeexplore.ieee.org/book/9198868 100 01 3100 https://ieeexplore.ieee.org/book/9198868 100 01 3100 für Uniangehörige: Zugang weltweit http://han.med.uni-magdeburg.de/han/mitvia-ieee/ieeexplore.ieee.org/book/9198868 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://ieeexplore.ieee.org/book/9198868 23 01 0830 2018-01805, 2018-01806, 2018-01808 22 01 0018 olrm-h228-MITIEEE 23 01 0830 olr-MIT 62 01 0028 OLR-MIT 100 01 3100 OLR-MIT-CEC 370 01 4370 olr-ebook mitieee 370 01 4370 2021.12.01 |
| allfields_unstemmed |
9780262358798 electronic bk. 978-0-262-35879-8 0262358786 0-262-35878-6 (DE-627)1860731376 (DE-599)KEP062309994 (OCoLC)1197707113 (MITPRESS)9198868 (EBP)062309994 DE-627 ger DE-627 rda eng 025.04 23 Schrage, Michael verfasserin aut Recommendation engines Michael Schrage Cambridge, Massachusetts The MIT Press 2020 1 PDF. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The MIT Press essential knowledge series Includes bibliographical references and index Restricted to subscribers or individual electronic text purchasers. "How does Netflix know just what to suggest you watch next? How does Amazon determine what a "customer like you" has also purchased? The answer is recommender systems, the technological concept that lies at the heart of most of the successful companies in the digital economy. Michael Schrage starts with the origins of recommender systems, which go back further than you think (see: the Oracle at Delphi for one of history's earliest recommenders), and a history of the first companies to harness recommendations. He then discusses the technology behind how recommenders work: the AI and machine learning algorithms that power these recommender platforms. Next he discusses the role of user experience, and how recommender systems are designed, and how design choices function as nudges to make certain recommendations more salient than others. He explores three case studies: Spotify, Bytedance, and Stitch Fix, looking at how recommenders can create new business solutions and how algorithms can go beyond curation to content creation. The concluding chapter on the future of recommender systems is perhaps the most enlightening. Moving away from technology and business, Schrage embraces the philosophical, probing the role of free will in a world mediated by recommender systems (a recommendation inherently offers a choice; without the element of choice, any digital manipulation of our preferences cannot truly be called a "recommendation"), and exploring the role of recommender systems as a means of improving the self. In the vein of Free Will, this book presents the essential information while revealing the author's point of view. Schrage wants to push our understanding of recommender systems beyond the technological, to understand what societal role they play and what opportunities they offer now and in the future"-- Mode of access: World Wide Web. Recommender systems (Information filtering) 9780262539074 Erscheint auch als Druck-Ausgabe 9780262539074 https://ieeexplore.ieee.org/book/9198868 X:MITPRESS Verlag lizenzpflichtig ZDB-37-IEM 2020 GBV_ILN_22 ISIL_DE-18 SYSFLAG_1 GBV_KXP GBV_ILN_22_i22818 GBV_ILN_23 ISIL_DE-830 GBV_ILN_62 ISIL_DE-28 GBV_ILN_100 ISIL_DE-Ma9 GBV_ILN_370 ISIL_DE-1373 BO 045F 025.04 22 01 0018 4391550474 olrm-h228-MITIEEE zi22818 17-10-23 23 01 0830 4391553562 olr-MIT i z 17-10-23 62 01 0028 4391568977 OLR-MIT Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. z 17-10-23 100 01 3100 4472471256 09 --%%-- eBook MIT Press --%%-- --%%-- OLR-MIT-CEC Vervielfältigungen (z.B. Kopien, Downloads) sind nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. z 30-01-24 370 01 4370 4391539012 olr-ebook mitieee Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 17-10-23 22 01 0018 Volltextzugang Campus https://ieeexplore.ieee.org/book/9198868 22 01 0018 Nur für Angehörige der Universität Hamburg: Volltextzugang von außerhalb des Campus http://emedien.sub.uni-hamburg.de/han/ieee/ieeexplore.ieee.org/book/9198868 23 01 0830 MIT Press EBook https://ieeexplore.ieee.org/book/9198868 62 01 0028 https://ieeexplore.ieee.org/book/9198868 100 01 3100 https://ieeexplore.ieee.org/book/9198868 100 01 3100 für Uniangehörige: Zugang weltweit http://han.med.uni-magdeburg.de/han/mitvia-ieee/ieeexplore.ieee.org/book/9198868 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://ieeexplore.ieee.org/book/9198868 23 01 0830 2018-01805, 2018-01806, 2018-01808 22 01 0018 olrm-h228-MITIEEE 23 01 0830 olr-MIT 62 01 0028 OLR-MIT 100 01 3100 OLR-MIT-CEC 370 01 4370 olr-ebook mitieee 370 01 4370 2021.12.01 |
| allfieldsGer |
9780262358798 electronic bk. 978-0-262-35879-8 0262358786 0-262-35878-6 (DE-627)1860731376 (DE-599)KEP062309994 (OCoLC)1197707113 (MITPRESS)9198868 (EBP)062309994 DE-627 ger DE-627 rda eng 025.04 23 Schrage, Michael verfasserin aut Recommendation engines Michael Schrage Cambridge, Massachusetts The MIT Press 2020 1 PDF. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The MIT Press essential knowledge series Includes bibliographical references and index Restricted to subscribers or individual electronic text purchasers. "How does Netflix know just what to suggest you watch next? How does Amazon determine what a "customer like you" has also purchased? The answer is recommender systems, the technological concept that lies at the heart of most of the successful companies in the digital economy. Michael Schrage starts with the origins of recommender systems, which go back further than you think (see: the Oracle at Delphi for one of history's earliest recommenders), and a history of the first companies to harness recommendations. He then discusses the technology behind how recommenders work: the AI and machine learning algorithms that power these recommender platforms. Next he discusses the role of user experience, and how recommender systems are designed, and how design choices function as nudges to make certain recommendations more salient than others. He explores three case studies: Spotify, Bytedance, and Stitch Fix, looking at how recommenders can create new business solutions and how algorithms can go beyond curation to content creation. The concluding chapter on the future of recommender systems is perhaps the most enlightening. Moving away from technology and business, Schrage embraces the philosophical, probing the role of free will in a world mediated by recommender systems (a recommendation inherently offers a choice; without the element of choice, any digital manipulation of our preferences cannot truly be called a "recommendation"), and exploring the role of recommender systems as a means of improving the self. In the vein of Free Will, this book presents the essential information while revealing the author's point of view. Schrage wants to push our understanding of recommender systems beyond the technological, to understand what societal role they play and what opportunities they offer now and in the future"-- Mode of access: World Wide Web. Recommender systems (Information filtering) 9780262539074 Erscheint auch als Druck-Ausgabe 9780262539074 https://ieeexplore.ieee.org/book/9198868 X:MITPRESS Verlag lizenzpflichtig ZDB-37-IEM 2020 GBV_ILN_22 ISIL_DE-18 SYSFLAG_1 GBV_KXP GBV_ILN_22_i22818 GBV_ILN_23 ISIL_DE-830 GBV_ILN_62 ISIL_DE-28 GBV_ILN_100 ISIL_DE-Ma9 GBV_ILN_370 ISIL_DE-1373 BO 045F 025.04 22 01 0018 4391550474 olrm-h228-MITIEEE zi22818 17-10-23 23 01 0830 4391553562 olr-MIT i z 17-10-23 62 01 0028 4391568977 OLR-MIT Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. z 17-10-23 100 01 3100 4472471256 09 --%%-- eBook MIT Press --%%-- --%%-- OLR-MIT-CEC Vervielfältigungen (z.B. Kopien, Downloads) sind nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. z 30-01-24 370 01 4370 4391539012 olr-ebook mitieee Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 17-10-23 22 01 0018 Volltextzugang Campus https://ieeexplore.ieee.org/book/9198868 22 01 0018 Nur für Angehörige der Universität Hamburg: Volltextzugang von außerhalb des Campus http://emedien.sub.uni-hamburg.de/han/ieee/ieeexplore.ieee.org/book/9198868 23 01 0830 MIT Press EBook https://ieeexplore.ieee.org/book/9198868 62 01 0028 https://ieeexplore.ieee.org/book/9198868 100 01 3100 https://ieeexplore.ieee.org/book/9198868 100 01 3100 für Uniangehörige: Zugang weltweit http://han.med.uni-magdeburg.de/han/mitvia-ieee/ieeexplore.ieee.org/book/9198868 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://ieeexplore.ieee.org/book/9198868 23 01 0830 2018-01805, 2018-01806, 2018-01808 22 01 0018 olrm-h228-MITIEEE 23 01 0830 olr-MIT 62 01 0028 OLR-MIT 100 01 3100 OLR-MIT-CEC 370 01 4370 olr-ebook mitieee 370 01 4370 2021.12.01 |
| allfieldsSound |
9780262358798 electronic bk. 978-0-262-35879-8 0262358786 0-262-35878-6 (DE-627)1860731376 (DE-599)KEP062309994 (OCoLC)1197707113 (MITPRESS)9198868 (EBP)062309994 DE-627 ger DE-627 rda eng 025.04 23 Schrage, Michael verfasserin aut Recommendation engines Michael Schrage Cambridge, Massachusetts The MIT Press 2020 1 PDF. Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The MIT Press essential knowledge series Includes bibliographical references and index Restricted to subscribers or individual electronic text purchasers. "How does Netflix know just what to suggest you watch next? How does Amazon determine what a "customer like you" has also purchased? The answer is recommender systems, the technological concept that lies at the heart of most of the successful companies in the digital economy. Michael Schrage starts with the origins of recommender systems, which go back further than you think (see: the Oracle at Delphi for one of history's earliest recommenders), and a history of the first companies to harness recommendations. He then discusses the technology behind how recommenders work: the AI and machine learning algorithms that power these recommender platforms. Next he discusses the role of user experience, and how recommender systems are designed, and how design choices function as nudges to make certain recommendations more salient than others. He explores three case studies: Spotify, Bytedance, and Stitch Fix, looking at how recommenders can create new business solutions and how algorithms can go beyond curation to content creation. The concluding chapter on the future of recommender systems is perhaps the most enlightening. Moving away from technology and business, Schrage embraces the philosophical, probing the role of free will in a world mediated by recommender systems (a recommendation inherently offers a choice; without the element of choice, any digital manipulation of our preferences cannot truly be called a "recommendation"), and exploring the role of recommender systems as a means of improving the self. In the vein of Free Will, this book presents the essential information while revealing the author's point of view. Schrage wants to push our understanding of recommender systems beyond the technological, to understand what societal role they play and what opportunities they offer now and in the future"-- Mode of access: World Wide Web. Recommender systems (Information filtering) 9780262539074 Erscheint auch als Druck-Ausgabe 9780262539074 https://ieeexplore.ieee.org/book/9198868 X:MITPRESS Verlag lizenzpflichtig ZDB-37-IEM 2020 GBV_ILN_22 ISIL_DE-18 SYSFLAG_1 GBV_KXP GBV_ILN_22_i22818 GBV_ILN_23 ISIL_DE-830 GBV_ILN_62 ISIL_DE-28 GBV_ILN_100 ISIL_DE-Ma9 GBV_ILN_370 ISIL_DE-1373 BO 045F 025.04 22 01 0018 4391550474 olrm-h228-MITIEEE zi22818 17-10-23 23 01 0830 4391553562 olr-MIT i z 17-10-23 62 01 0028 4391568977 OLR-MIT Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. z 17-10-23 100 01 3100 4472471256 09 --%%-- eBook MIT Press --%%-- --%%-- OLR-MIT-CEC Vervielfältigungen (z.B. Kopien, Downloads) sind nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. z 30-01-24 370 01 4370 4391539012 olr-ebook mitieee Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 17-10-23 22 01 0018 Volltextzugang Campus https://ieeexplore.ieee.org/book/9198868 22 01 0018 Nur für Angehörige der Universität Hamburg: Volltextzugang von außerhalb des Campus http://emedien.sub.uni-hamburg.de/han/ieee/ieeexplore.ieee.org/book/9198868 23 01 0830 MIT Press EBook https://ieeexplore.ieee.org/book/9198868 62 01 0028 https://ieeexplore.ieee.org/book/9198868 100 01 3100 https://ieeexplore.ieee.org/book/9198868 100 01 3100 für Uniangehörige: Zugang weltweit http://han.med.uni-magdeburg.de/han/mitvia-ieee/ieeexplore.ieee.org/book/9198868 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://ieeexplore.ieee.org/book/9198868 23 01 0830 2018-01805, 2018-01806, 2018-01808 22 01 0018 olrm-h228-MITIEEE 23 01 0830 olr-MIT 62 01 0028 OLR-MIT 100 01 3100 OLR-MIT-CEC 370 01 4370 olr-ebook mitieee 370 01 4370 2021.12.01 |
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"How does Netflix know just what to suggest you watch next? How does Amazon determine what a "customer like you" has also purchased? The answer is recommender systems, the technological concept that lies at the heart of most of the successful companies in the digital economy. Michael Schrage starts with the origins of recommender systems, which go back further than you think (see: the Oracle at Delphi for one of history's earliest recommenders), and a history of the first companies to harness recommendations. He then discusses the technology behind how recommenders work: the AI and machine learning algorithms that power these recommender platforms. Next he discusses the role of user experience, and how recommender systems are designed, and how design choices function as nudges to make certain recommendations more salient than others. He explores three case studies: Spotify, Bytedance, and Stitch Fix, looking at how recommenders can create new business solutions and how algorithms can go beyond curation to content creation. The concluding chapter on the future of recommender systems is perhaps the most enlightening. Moving away from technology and business, Schrage embraces the philosophical, probing the role of free will in a world mediated by recommender systems (a recommendation inherently offers a choice; without the element of choice, any digital manipulation of our preferences cannot truly be called a "recommendation"), and exploring the role of recommender systems as a means of improving the self. In the vein of Free Will, this book presents the essential information while revealing the author's point of view. Schrage wants to push our understanding of recommender systems beyond the technological, to understand what societal role they play and what opportunities they offer now and in the future"-- Includes bibliographical references and index |
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