Reality mining: using big data to engineer a better world
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge, Massachusetts
The MIT Press
[2014]
|
| Schlagworte: | |
| Beschreibung: | Print version record |
| Beschreibung: | 1 online resource (vi, 199 pages) |
| ISBN: | 9780262324564 0262324563 9780262324571 0262324571 |
Internformat
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| 505 | 8 | |a In this book, the authors explore the positive potential of big data, showing the ways in which the analysis of big data ("reality mining") can be used to improve human systems as varied as political polling and disease tracking, while considering user privacy. They describe reality mining at five different levels: the individual, the neighborhood and organization, the city, the nation, and the world. For each level, they offer a nontechnical explanation of data collection methods and describe applications and systems that have been or could be built. These include a mobile app that helps smokers quit smoking; a workplace "knowledge system"; the use of GPS, Wi-Fi, and mobile phone data to manage and predict traffic flows; and the analysis of social media to track the spread of disease. The authors argue that big data, used respectfully and responsibly, can help people live better, healthier, and happier lives. -- | |
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Datensatz im Suchindex
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| author | Eagle, Nathan |
| author_facet | Eagle, Nathan |
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| contents | In this book, the authors explore the positive potential of big data, showing the ways in which the analysis of big data ("reality mining") can be used to improve human systems as varied as political polling and disease tracking, while considering user privacy. They describe reality mining at five different levels: the individual, the neighborhood and organization, the city, the nation, and the world. For each level, they offer a nontechnical explanation of data collection methods and describe applications and systems that have been or could be built. These include a mobile app that helps smokers quit smoking; a workplace "knowledge system"; the use of GPS, Wi-Fi, and mobile phone data to manage and predict traffic flows; and the analysis of social media to track the spread of disease. The authors argue that big data, used respectfully and responsibly, can help people live better, healthier, and happier lives. -- |
| ctrlnum | (ZDB-4-ITC)ocn886539978 (OCoLC)886539978 (DE-599)BVBBV045350827 |
| dewey-full | 006.3/12 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 006 - Special computer methods |
| dewey-raw | 006.3/12 |
| dewey-search | 006.3/12 |
| dewey-sort | 16.3 212 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Informatik |
| format | Electronic eBook |
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| indexdate | 2024-07-10T08:15:42Z |
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| language | English |
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| spelling | Eagle, Nathan Verfasser aut Reality mining using big data to engineer a better world by Nathan Eagle and Kate Greene Cambridge, Massachusetts The MIT Press [2014] 2014 1 online resource (vi, 199 pages) txt rdacontent c rdamedia cr rdacarrier Print version record In this book, the authors explore the positive potential of big data, showing the ways in which the analysis of big data ("reality mining") can be used to improve human systems as varied as political polling and disease tracking, while considering user privacy. They describe reality mining at five different levels: the individual, the neighborhood and organization, the city, the nation, and the world. For each level, they offer a nontechnical explanation of data collection methods and describe applications and systems that have been or could be built. These include a mobile app that helps smokers quit smoking; a workplace "knowledge system"; the use of GPS, Wi-Fi, and mobile phone data to manage and predict traffic flows; and the analysis of social media to track the spread of disease. The authors argue that big data, used respectfully and responsibly, can help people live better, healthier, and happier lives. -- COMPUTERS / General bisacsh COMPUTERS / Database Management / Data Mining bisacsh Big data fast Computer networks / Social aspects fast Data mining fast Information science / Social aspects fast Information science / Statistical methods fast Data mining Big data Computer networks Social aspects Information science Social aspects Information science Statistical methods Data Mining (DE-588)4428654-5 gnd rswk-swf Big Data (DE-588)4802620-7 gnd rswk-swf Personenbezogene Daten (DE-588)4173908-5 gnd rswk-swf Technikbewertung (DE-588)4078176-8 gnd rswk-swf Data Mining (DE-588)4428654-5 s Big Data (DE-588)4802620-7 s Personenbezogene Daten (DE-588)4173908-5 s Technikbewertung (DE-588)4078176-8 s 1\p DE-604 Greene, Kate 1979- Sonstige oth Erscheint auch als Druck-Ausgabe Eagle, Nathan Reality mining 9780262027687 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Eagle, Nathan Reality mining using big data to engineer a better world In this book, the authors explore the positive potential of big data, showing the ways in which the analysis of big data ("reality mining") can be used to improve human systems as varied as political polling and disease tracking, while considering user privacy. They describe reality mining at five different levels: the individual, the neighborhood and organization, the city, the nation, and the world. For each level, they offer a nontechnical explanation of data collection methods and describe applications and systems that have been or could be built. These include a mobile app that helps smokers quit smoking; a workplace "knowledge system"; the use of GPS, Wi-Fi, and mobile phone data to manage and predict traffic flows; and the analysis of social media to track the spread of disease. The authors argue that big data, used respectfully and responsibly, can help people live better, healthier, and happier lives. -- COMPUTERS / General bisacsh COMPUTERS / Database Management / Data Mining bisacsh Big data fast Computer networks / Social aspects fast Data mining fast Information science / Social aspects fast Information science / Statistical methods fast Data mining Big data Computer networks Social aspects Information science Social aspects Information science Statistical methods Data Mining (DE-588)4428654-5 gnd Big Data (DE-588)4802620-7 gnd Personenbezogene Daten (DE-588)4173908-5 gnd Technikbewertung (DE-588)4078176-8 gnd |
| subject_GND | (DE-588)4428654-5 (DE-588)4802620-7 (DE-588)4173908-5 (DE-588)4078176-8 |
| title | Reality mining using big data to engineer a better world |
| title_auth | Reality mining using big data to engineer a better world |
| title_exact_search | Reality mining using big data to engineer a better world |
| title_full | Reality mining using big data to engineer a better world by Nathan Eagle and Kate Greene |
| title_fullStr | Reality mining using big data to engineer a better world by Nathan Eagle and Kate Greene |
| title_full_unstemmed | Reality mining using big data to engineer a better world by Nathan Eagle and Kate Greene |
| title_short | Reality mining |
| title_sort | reality mining using big data to engineer a better world |
| title_sub | using big data to engineer a better world |
| topic | COMPUTERS / General bisacsh COMPUTERS / Database Management / Data Mining bisacsh Big data fast Computer networks / Social aspects fast Data mining fast Information science / Social aspects fast Information science / Statistical methods fast Data mining Big data Computer networks Social aspects Information science Social aspects Information science Statistical methods Data Mining (DE-588)4428654-5 gnd Big Data (DE-588)4802620-7 gnd Personenbezogene Daten (DE-588)4173908-5 gnd Technikbewertung (DE-588)4078176-8 gnd |
| topic_facet | COMPUTERS / General COMPUTERS / Database Management / Data Mining Big data Computer networks / Social aspects Data mining Information science / Social aspects Information science / Statistical methods Data mining Big data Computer networks Social aspects Information science Social aspects Information science Statistical methods Data Mining Big Data Personenbezogene Daten Technikbewertung |
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