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Which clippings match 'Data Matching' keyword pg.1 of 1
04 JANUARY 2014

An introduction to recommender systems

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TAGS

advogato.org • affinity analysisalgorithmic filtersAmazon.comautomatic predictions • collaborative filtering • collaborative filtering approach • correlationsdata matchingdata miningecho chamberfavourite things • FilmTrust • information filtering • information filtering system • information patterns • interests • Jennifer Golbeck • large datasetsLast.fm • moleskiing.it • Pandora Radiopersonal tastepersonalised suggestionsprediction • process of filtering • rating systemrecommendationrecommendation enginerecommendation platform • recommendation system • recommendation systems • recommender systems • relatednessrelationships between individualsserendipitysimilaritysimilarity machinesimilitude • trust metric • trust-based recommender systems • user datauser preferences

CONTRIBUTOR

Simon Perkins
01 JANUARY 2014

Tinder: swiping yes to intimate invitations from relative strangers

"Tinder uses your existing social networking data from Facebook to locate people in the immediate vicinity, tell you a bit about them, whether you have any friends in common and (most importantly) show you a pic.

It has slimmed down the emotional, cognitive and financial investment required by the virtual dating process to one simple question: 'Do I want to do you?' What more modern way to make that most basic binary decision of whether you want to shag someone than a game of real–world 'Hot or Not'?

Social media has made us expert first–daters, well–versed in smalltalk and over–sharing with strangers. The quick follow–though from swipe to sex is similarly instinctive for a generation with an appetite for immediacy."

(Caroline Kent, 19 Sep 2013)

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TAGS

automatic predictions • binary decision • casual sexcommodifying myselfcomparison site • compass • cross-context sharingdatadata matchingdatingFacebook • friends in common • hot or not • identity performance • immediate vicinity • iPhonelikedlikeslocation-basedlocation-based social networkingmobile appnormalising over-sharingonline datingonline profilesoversharingpersonal brandingproximityrecommendation platformself-disclosure • shag • shared friends • small talksocial mediasocial networkingspectacular societyswipingTinder (app)user data • vicinity • virtual dating

CONTRIBUTOR

Simon Perkins
25 SEPTEMBER 2011

Every click you make, Facebook tracker will be watching you

"Facebook also introduced new features aimed at marketing companies that let users monitor what their fellow members are watching and listening to online instantly. ...

'Retention of information online has always been a problem. If information comes and goes fleetingly there's less likelihood it will be used other than for the purpose you put it up, which is just to keep people in touch with what you're doing,' Mr Vaile said.

'This is in line with my concern about Facebook trying to change how people think and encourage them to normalise over–sharing and abandon any restraint on storage and use and exposure of private information.'"

(Andrew Colley, 24 September 2011, The Australian)

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TAGS

abandon restraint • autonomycommercial exploitationcommodifying myselfcommodityconductconstruction of normscontextcross-context sharing • cyber-communities • cyberspacedatadata matchingdemassificationdigital identity • digital maps • digital representation • digital signature • e-privacyethicsexposureFacebook • Facebook tracker • human interactioninformationinformation sharingmonitoringnormalisationnormalising over-sharingonlineownershippersonal informationprivacy • privacy watchdog • publicly availableretention of informationsocial networkingstoragetechnological innovation • they are watching you • timeline • Timothy Pilgrim • trackerUNSWuse of private information • use their information • what you are watching

CONTRIBUTOR

Simon Perkins
24 MARCH 2009

data-sharing and multi-agency working

"A proliferation of IT systems has meant information relating to the same person is often held in multiple systems. Dependent upon the services they receive, Case Workers may well have to access a number of systems in an attempt to get a better picture of the circumstances of each client. This way of working relies on the Case Worker undertaking these searches – something which time pressured staff may not have the time to do. The result is that potentially only a partial picture can be painted with vital issues being missed, therefore completely compromising the decision making.

The drive towards a more person centred approach to service delivery means that the complete picture of a client's circumstances becomes an essential requirement. The introduction of multi–agency working has moved this agenda on somewhat, but the scope of work to date has been restricted to a limited number of agencies often with a history of working together. Broadening the reach of multi–agency working means concerns about data sharing and client confidentiality are issues which have to be robustly addressed for solutions to be trusted and the benefits realised."
(Liquidlogic)

TAGS

case worker • childconfidential • connecting the dots • cross-context sharingdatadata matching • multi-agency working • personal dataprivacy • PROTOCOL 360 • welfare

CONTRIBUTOR

Simon Perkins
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