| 000 | 05139nam a2201237 i 4500 | ||
|---|---|---|---|
| 001 | 6926931 | ||
| 003 | IEEE | ||
| 005 | 20190220121651.0 | ||
| 006 | m o d | ||
| 007 | cr |n||||||||| | ||
| 008 | 151223s2014 mau ob 001 eng d | ||
| 020 |
_a9780262324564 _qelectronic |
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| 020 |
_z0262027682 _qhardcover : alk. paper |
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| 020 |
_z9780262027687 _qhardcover : alk. paper |
||
| 020 |
_z0262324563 _qelectronic |
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| 035 | _a(CaBNVSL)mat06926931 | ||
| 035 | _a(IDAMS)0b000064827e0bde | ||
| 040 |
_aCaBNVSL _beng _erda _cCaBNVSL _dCaBNVSL |
||
| 050 | 4 |
_aQA76.9.D343 _bE24 2014eb |
|
| 082 | 0 | 4 |
_a006.3/12 _223 |
| 100 | 1 |
_aEagle, Nathan, _eauthor. |
|
| 245 | 1 | 0 |
_aReality mining : _busing big data to engineer a better world / _cby Nathan Eagle and Kate Greene. |
| 264 | 1 |
_aCambridge, Massachusetts : _bMIT Press, _c[2014] |
|
| 264 | 2 |
_a[Piscataqay, New Jersey] : _bIEEE Xplore, _c[2014] |
|
| 300 | _a1 PDF (208 pages). | ||
| 336 |
_atext _2rdacontent |
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| 337 |
_aelectronic _2isbdmedia |
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| 338 |
_aonline resource _2rdacarrier |
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| 504 | _aIncludes bibliographical references and index. | ||
| 506 | 1 | _aRestricted to subscribers or individual electronic text purchasers. | |
| 520 | _aBig Data is made up of lots of little data: numbers entered into cell phones, addresses entered into GPS devices, visits to websites, online purchases, ATM transactions, and any other activity that leaves a digital trail. Although the abuse of Big Data -- surveillance, spying, hacking -- has made headlines, it shouldn't overshadow the abundant positive applications of Big Data. In Reality Mining, Nathan Eagle and Kate Greene cut through the hype and the headlines to 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.Eagle, a recognized expert in the field, and Greene, an experienced technology journalist, describe Reality Mining at five different levels: the individual, the neighborhood and organization, the city, the nation, and the world. For each level, they first offer a nontechnical explanation of data collection methods and then 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. Eagle and Greene argue that Big Data, used respectfully and responsibly, can help people live better, healthier, and happier lives. | ||
| 530 | _aAlso available in print. | ||
| 538 | _aMode of access: World Wide Web | ||
| 588 | _aDescription based on PDF viewed 12/23/2015. | ||
| 650 | 0 |
_aInformation science _xStatistical methods. |
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| 650 | 0 |
_aInformation science _xSocial aspects. |
|
| 650 | 0 |
_aComputer networks _xSocial aspects. |
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| 650 | 0 | _aBig data. | |
| 650 | 0 | _aData mining. | |
| 655 | 0 | _aElectronic books. | |
| 695 | _aAccidents | ||
| 695 | _aAtmospheric modeling | ||
| 695 | _aBig data | ||
| 695 | _aBiomedical monitoring | ||
| 695 | _aBiosensors | ||
| 695 | _aBuildings | ||
| 695 | _aBusiness | ||
| 695 | _aCameras | ||
| 695 | _aCities and towns | ||
| 695 | _aCompanies | ||
| 695 | _aComputers | ||
| 695 | _aData analysis | ||
| 695 | _aData collection | ||
| 695 | _aData mining | ||
| 695 | _aData models | ||
| 695 | _aData privacy | ||
| 695 | _aData visualization | ||
| 695 | _aDatabases | ||
| 695 | _aDiseases | ||
| 695 | _aEconomics | ||
| 695 | _aEducational institutions | ||
| 695 | _aElectronic mail | ||
| 695 | _aEmployment | ||
| 695 | _aFacebook | ||
| 695 | _aFires | ||
| 695 | _aGlobal Positioning System | ||
| 695 | _aGoogle | ||
| 695 | _aGovernment | ||
| 695 | _aIndexes | ||
| 695 | _aInsurance | ||
| 695 | _aIntelligent sensors | ||
| 695 | _aInternet | ||
| 695 | _aMarket research | ||
| 695 | _aMathematical model | ||
| 695 | _aMedical services | ||
| 695 | _aMobile communication | ||
| 695 | _aMobile handsets | ||
| 695 | _aMonitoring | ||
| 695 | _aNavigation | ||
| 695 | _aOrganizations | ||
| 695 | _aPervasive computing | ||
| 695 | _aPredictive models | ||
| 695 | _aPresses | ||
| 695 | _aPrivacy | ||
| 695 | _aPsychology | ||
| 695 | _aRadiofrequency identification | ||
| 695 | _aResource management | ||
| 695 | _aRoads | ||
| 695 | _aSensors | ||
| 695 | _aSocial network services | ||
| 695 | _aSociology | ||
| 695 | _aSoftware | ||
| 695 | _aStandards organizations | ||
| 695 | _aStatistics | ||
| 695 | _aTracking | ||
| 695 | _aTwitter | ||
| 695 | _aVectors | ||
| 695 | _aVehicles | ||
| 695 | _aWorld Wide Web | ||
| 695 | _aWriting | ||
| 700 | 1 |
_aGreene, Kate, _d1979-, _eauthor. |
|
| 710 | 2 |
_aIEEE Xplore (Online Service), _edistributor. |
|
| 710 | 2 |
_aMIT Press, _epublisher. |
|
| 776 | 0 | 8 |
_iPrint version _z9780262027687 |
| 856 | 4 | 2 |
_3Abstract with links to resource _uhttp://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=6926931 |
| 999 |
_c39643 _d39643 |
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