Publication
Big Data analysis applied to the retail sector
| dc.contributor.author | Barata, Luís | |
| dc.contributor.author | Rosa, Gonçalo | |
| dc.contributor.author | Martins, Tiago | |
| dc.contributor.author | Silva, Pedro Tiago Salgueiro da | |
| dc.contributor.author | Eurico, Lopes | |
| dc.date.accessioned | 2024-12-19T11:31:00Z | |
| dc.date.available | 2024-12-19T11:31:00Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | Big Data and Artificial Intelligence are rapidly evolving and transforming the world and e-commerce. To explore the most used techniques for building personalized recommendation systems and inventory management, a systematic review was conducted. It was found that hybrid Machine Learning techniques and the Hadoop system are widely used in these areas, delivering satisfactory results while maintaining scalable and efficient systems. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.citation | BARATA, Luis [et al.] (2024) - Big Data analysis applied to the retail sector. In Mediterranean Conference on Information Systems 2024, Porto - Proceedings. 41. https://aisel.aisnet.org/mcis2024/41 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10400.11/9245 | |
| dc.language.iso | eng | pt_PT |
| dc.peerreviewed | yes | pt_PT |
| dc.relation.publisherversion | https://aisel.aisnet.org/mcis2024/41 | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | pt_PT |
| dc.subject | Big Data | pt_PT |
| dc.subject | Data analytics | pt_PT |
| dc.subject | Personalization of recommendations | pt_PT |
| dc.subject | Stock management | pt_PT |
| dc.title | Big Data analysis applied to the retail sector | pt_PT |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.citation.conferencePlace | Porto, Portugal | pt_PT |
| oaire.citation.title | Mediterranean Conference on Information Systems (MCIS) | pt_PT |
| person.familyName | Lopes | |
| person.givenName | Eurico | |
| person.identifier.ciencia-id | 281C-B830-CF30 | |
| person.identifier.ciencia-id | C117-F943-3B96 | |
| person.identifier.orcid | 0000-0002-6471-4681 | |
| person.identifier.orcid | 0000-0002-1818-8203 | |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | article | pt_PT |
| relation.isAuthorOfPublication | eb1ed459-bdc5-42b3-a6aa-1d79caeabdcc | |
| relation.isAuthorOfPublication | 9c74d9ee-6c71-4148-b219-2795a71a4d1b | |
| relation.isAuthorOfPublication.latestForDiscovery | eb1ed459-bdc5-42b3-a6aa-1d79caeabdcc |
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