# name
Identification of negative keywords in search marketing with embedding layers and neural networks

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Treballs finals del Màster de Fonaments de Ciència de Dades, Facultat de matemàtiques, Universitat de Barcelona. Any: 2021. Tutor: Jordi Vitrià i Marca

# metadata.dc.description.abstract[].value
[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.

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Màster Oficial - Fonaments de la Ciència de Dades

# metadata.dc.title[].value
Identification of negative keywords in search marketing with embedding layers and neural networks