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Title: Identification of negative keywords in search marketing with embedding layers and neural networks
Author: Loris, David
Director/Tutor: Vitrià i Marca, Jordi
Keywords: Publicitat per Internet
Xarxes neuronals (Informàtica)
Cerca a Internet
Treballs de fi de màster
Internet advertising
Neural networks (Computer science)
Internet searching
Master's theses
Issue Date: 18-Jan-2021
Abstract: [en] In this paper we introduce a model to help marketing specialists within the field of Search Advertising to limit spend on Google searches which have a low probability of leading to a revenue generating event. This is a topic which has not been widely addressed in scientific literature. For this study, we obtained data from a company which spends a large amount on Google Ads, but relies on a subjective and time-consuming approach to this problem. Our proposed model uses GloVe’s pre-trained Embedding Layers and Neural Networks to speed up and improve accuracy of this process.
Note: Treballs finals del Màster de Fonaments de Ciència de Dades, Facultat de matemàtiques, Universitat de Barcelona. Any: 2021. Tutor: Jordi Vitrià i Marca
Appears in Collections:Màster Oficial - Fonaments de la Ciència de Dades

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