Please use this identifier to cite or link to this item:
http://hdl.handle.net/2445/183339
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 |
URI: | http://hdl.handle.net/2445/183339 |
Appears in Collections: | Màster Oficial - Fonaments de la Ciència de Dades |
Files in This Item:
File | Description | Size | Format | |
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tfm_david_loris.pdf | Memòria | 1.08 MB | Adobe PDF | View/Open |
README.md | readme.md | 1.05 kB | Unknown | View/Open |
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