Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Melinda Han Williams"'
Autor:
White Amelia Grieve, Chris Jenness, Justin Moynihan, Jason R. Kaufman, Roger Cost, Patrick McCarthy, Wickus Martin, Melinda Han Williams
Publikováno v:
IEEE BigData
Today, predictive digital ad targeting typically relies on detailed user profiles. As consumers deserve and expect more internet privacy, we aim to develop methods to effectively target advertising in a way that respects consumers’ wishes. In parti
Autor:
Peter Lenz, Melinda Han Williams, Yeming Shi, Roger Cost, Rod Hook, Patrick McCarthy, Reka Daniel-Weiner, Claudia Perlich, Wickus Martin, Justin Moynihan
Publikováno v:
KDD
A growing proportion of digital advertising slots is purchased through real time bidding auctions, which enables advertisers to impose highly specific criteria on which devices and opportunities to target. Employing sophisticated targeting criteria r
Autor:
Brian Dalessandro, Melinda Han Williams, Claudia Perlich, Daizhuo Chen, Troy Raeder, Foster Provost
Publikováno v:
KDD
Internet display advertising is a critical revenue source for publishers and online content providers, and is supported by massive amounts of user and publisher data. Targeting display ads can be improved substantially with machine learning methods,
Publikováno v:
ADKDD@KDD
Most video advertising campaigns today are still evaluated based on aggregate demographic audience metrics, rather than measures of individual impact or even individual demographic reach. To fit in with advertisers' evaluations, campaigns must be opt