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Stochastic Blockmodeling for Online Advertising
[article]
2014
arXiv
pre-print
Online advertising is an important and huge industry. Having knowledge of the website attributes can contribute greatly to business strategies for ad-targeting, content display, inventory purchase or revenue prediction. Classical inferences on users and sites impose challenge, because the data is voluminous, sparse, high-dimensional and noisy. In this paper, we introduce a stochastic blockmodeling for the website relations induced by the event of online user visitation. We propose two
arXiv:1410.6714v2
fatcat:5nebqrgxbjci7o7hailsqm4mve