Publicação
Exploring product entity matching in a multi-domain landscape - a graph neural network approach
| datacite.subject.fos | Ciências Sociais::Economia e Gestão | pt_PT |
| dc.contributor.advisor | Han, Qiwei | |
| dc.contributor.author | Almeida, Miguel Barata Serrano Gonçalves de | |
| dc.date.accessioned | 2024-10-29T10:19:52Z | |
| dc.date.available | 2024-10-29T10:19:52Z | |
| dc.date.issued | 2024-01-17 | |
| dc.date.submitted | 2023-12-20 | |
| dc.description.abstract | This paper explores entity matching and its vital role in e-commerce to track products across different domains. Focusing on five diverse approaches, we evaluate their performance based on the precision to recall trade-off. The GNN model is examined theoretically, emphasizing its advantages and limitations. I also discuss potential improvements to enhance its applicability in this field. This research aims to provide deeper insights into the effectiveness of various entity matching strategies and their performance under distinct priorities, while considering model architecture and room for improvement. | pt_PT |
| dc.identifier.tid | 203605667 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10362/174226 | |
| dc.language.iso | eng | pt_PT |
| dc.relation | UID/ECO/00124/2013 | pt_PT |
| dc.subject | Entity matching | pt_PT |
| dc.subject | Record linkage | pt_PT |
| dc.subject | Data linkage | pt_PT |
| dc.subject | Entity resolution | pt_PT |
| dc.subject | E-commerce | pt_PT |
| dc.subject | Machine learning | pt_PT |
| dc.subject | Nlp | pt_PT |
| dc.subject | Gnn | pt_PT |
| dc.title | Exploring product entity matching in a multi-domain landscape - a graph neural network approach | pt_PT |
| dc.type | master thesis | |
| dspace.entity.type | Publication | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | masterThesis | pt_PT |
| thesis.degree.name | A Work Project, presented as part of the requirements for the Award of a Master’s degree in Business Analytics from the Nova School of Business and Economics. | pt_PT |