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Title: Predicción de pujas en publicidad programática
Author: Pérez Romero, Marta
Tutor: Andrés Sanz, Humberto
Keywords: business intelligence
machine learning
artificial intelligence
Issue Date: 6-Jun-2022
Publisher: Universitat Oberta de Catalunya (UOC)
Abstract: Machine Learning can be applied to different fields and for different purposes. In this TFG this will be applied to internet advertising. This is where the second part of the proposal comes into play. Since the beginning of online advertising, with the pay-per-click model, the forms of internet advertising have been increasing, segregating the market into different solutions. One of them is programmatic advertising. It is based on the existence of advertisers and publishers. The former want to advertise their product or service, while publishers sell their advertising space. In this TFG the company Kimia will help by providing a dataset with real data, from which the application of ML to this real environment can be made. The problem is that the company sends the available ads to its publisher network. Networks or publishers assess whether they are interested in entering an auction and bidding on those ads or not. This decision depends on factors such as the type of ad, its segment, the price from which it starts, etc. The company Kimia has an analysis of which networks or publishers are more profitable and suitable for the business (they provide quality traffic). In this way, the ideal is that the company sends the ads only to those networks that are more likely to accept that ad and give greater profitability. And this is where the TFG can provide a highvalue proposition.
Language: Spanish
Appears in Collections:Bachelor thesis, research projects, etc.

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