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Recommendation Engines
Taschenbuch von Michael Schrage
Sprache: Englisch

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Beschreibung
How companies like Amazon and Netflix know what "you might also like”: the history, technology, business, and social impact of online recommendation engines.

Increasingly, our technologies are giving us better, faster, smarter, and more personal advice than our own families and best friends. Amazon already knows what kind of books and household goods you like and is more than eager to recommend more; YouTube and TikTok always have another video lined up to show you; Netflix has crunched the numbers of your viewing habits to suggest whole genres that you would enjoy. In this volume in the MIT Press's Essential Knowledge series, innovation expert Michael Schrage explains the origins, technologies, business applications, and increasing societal impact of recommendation engines, the systems that allow companies worldwide to know what products, services, and experiences "you might also like.”

Schrage offers a history of recommendation that reaches back to antiquity's oracles and astrologers; recounts the academic origins and commercial evolution of recommendation engines; explains how these systems work, discussing key mathematical insights, including the impact of machine learning and deep learning algorithms; and highlights user experience design challenges. He offers brief but incisive case studies of the digital music service Spotify; ByteDance, the owner of TikTok; and the online personal stylist Stitch Fix. Finally, Schrage considers the future of technological recommenders: Will they leave us disappointed and dependent—or will they help us discover the world and ourselves in novel and serendipitous ways?

How companies like Amazon and Netflix know what "you might also like”: the history, technology, business, and social impact of online recommendation engines.

Increasingly, our technologies are giving us better, faster, smarter, and more personal advice than our own families and best friends. Amazon already knows what kind of books and household goods you like and is more than eager to recommend more; YouTube and TikTok always have another video lined up to show you; Netflix has crunched the numbers of your viewing habits to suggest whole genres that you would enjoy. In this volume in the MIT Press's Essential Knowledge series, innovation expert Michael Schrage explains the origins, technologies, business applications, and increasing societal impact of recommendation engines, the systems that allow companies worldwide to know what products, services, and experiences "you might also like.”

Schrage offers a history of recommendation that reaches back to antiquity's oracles and astrologers; recounts the academic origins and commercial evolution of recommendation engines; explains how these systems work, discussing key mathematical insights, including the impact of machine learning and deep learning algorithms; and highlights user experience design challenges. He offers brief but incisive case studies of the digital music service Spotify; ByteDance, the owner of TikTok; and the online personal stylist Stitch Fix. Finally, Schrage considers the future of technological recommenders: Will they leave us disappointed and dependent—or will they help us discover the world and ourselves in novel and serendipitous ways?

Über den Autor
Michael Schrage is a Research Fellow at the MIT Sloan School of Management's Initiative on the Digital Economy. A sought-after expert on innovation, design, and network effects, he is the author of Serious Play: How the World's Best Companies Simulate to Innovate, The Innovator's Hypothesis: How Cheap Experiments Are Worth More than Good Ideas (MIT Press), and other books.
Inhaltsverzeichnis
Series Foreword vii
Introduction ix
1 What Recommenders Are/Why Recommenders Matter 1
2 On the Origins of Recommendation 35
3 A Brief History of Recommendation Engines 63
4 How Recommenders Work 109
5 Experiencing Recommendations 149
6 Recommendation Innovators 177
7 The Recommender Future 211
Acknowledgments 241
Glossary 245
Notes 251
Further Reading 261
Index 263
Details
Erscheinungsjahr: 2020
Genre: Importe, Technik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: Einband - flex.(Paperback)
ISBN-13: 9780262539074
ISBN-10: 0262539071
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Schrage, Michael
Hersteller: MIT Press Ltd
Verantwortliche Person für die EU: preigu, Ansas Meyer, Lengericher Landstr. 19, D-49078 Osnabrück, mail@preigu.de
Maße: 178 x 128 x 24 mm
Von/Mit: Michael Schrage
Erscheinungsdatum: 01.09.2020
Gewicht: 0,277 kg
Artikel-ID: 118033659
Über den Autor
Michael Schrage is a Research Fellow at the MIT Sloan School of Management's Initiative on the Digital Economy. A sought-after expert on innovation, design, and network effects, he is the author of Serious Play: How the World's Best Companies Simulate to Innovate, The Innovator's Hypothesis: How Cheap Experiments Are Worth More than Good Ideas (MIT Press), and other books.
Inhaltsverzeichnis
Series Foreword vii
Introduction ix
1 What Recommenders Are/Why Recommenders Matter 1
2 On the Origins of Recommendation 35
3 A Brief History of Recommendation Engines 63
4 How Recommenders Work 109
5 Experiencing Recommendations 149
6 Recommendation Innovators 177
7 The Recommender Future 211
Acknowledgments 241
Glossary 245
Notes 251
Further Reading 261
Index 263
Details
Erscheinungsjahr: 2020
Genre: Importe, Technik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: Einband - flex.(Paperback)
ISBN-13: 9780262539074
ISBN-10: 0262539071
Sprache: Englisch
Einband: Kartoniert / Broschiert
Autor: Schrage, Michael
Hersteller: MIT Press Ltd
Verantwortliche Person für die EU: preigu, Ansas Meyer, Lengericher Landstr. 19, D-49078 Osnabrück, mail@preigu.de
Maße: 178 x 128 x 24 mm
Von/Mit: Michael Schrage
Erscheinungsdatum: 01.09.2020
Gewicht: 0,277 kg
Artikel-ID: 118033659
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