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dc.contributor.author | Palomino, Arturo | es_ES |
dc.contributor.author | Gibert, Karina | es_ES |
dc.date.accessioned | 2024-01-11T08:45:21Z | |
dc.date.available | 2024-01-11T08:45:21Z | |
dc.date.issued | 2023-09-22 | |
dc.identifier.isbn | 9788413960869 | |
dc.identifier.uri | http://hdl.handle.net/10251/201765 | |
dc.description.abstract | [EN] Chained advertisement involves breaking down a marketing campaign message into multiple banners that are shown to a user in a specific sequence in order to create a less intrusive and more effective campaign. The challenge is determining the most effective sequence of websites and banner order. This study aims to develop a recommendation system to assist with this issue. To address the vast size of the internet and the complexity of the problem, the research uses a data-driven computational approach to estimate the probability of different sequence events and apply this to real user data from a leading company. The proposed method is faster and more efficient than previous approaches. | es_ES |
dc.format.extent | 11 | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Editorial Universitat Politècnica de València | es_ES |
dc.relation.ispartof | 5th International Conference on Advanced Research Methods and Analytics (CARMA 2023) | |
dc.rights | Reconocimiento - No comercial - Compartir igual (by-nc-sa) | es_ES |
dc.subject | User-centric clickstream | es_ES |
dc.subject | Sequence | es_ES |
dc.subject | Profiling | es_ES |
dc.subject | Chained advertisement | es_ES |
dc.subject | Recommender systems | es_ES |
dc.subject | Probability | es_ES |
dc.title | Finding patterns from a user-centric perspective using knowledge discovery methods | es_ES |
dc.type | Capítulo de libro | es_ES |
dc.type | Comunicación en congreso | es_ES |
dc.identifier.doi | 10.4995/CARMA2023.2023.16041 | |
dc.rights.accessRights | Abierto | es_ES |
dc.description.bibliographicCitation | Palomino, A.; Gibert, K. (2023). Finding patterns from a user-centric perspective using knowledge discovery methods. Editorial Universitat Politècnica de València. 307-317. https://doi.org/10.4995/CARMA2023.2023.16041 | es_ES |
dc.description.accrualMethod | OCS | es_ES |
dc.relation.conferencename | CARMA 2023 - 5th International Conference on Advanced Research Methods and Analytics | es_ES |
dc.relation.conferencedate | Junio 28-30, 2023 | es_ES |
dc.relation.conferenceplace | Sevilla, España | es_ES |
dc.relation.publisherversion | http://ocs.editorial.upv.es/index.php/CARMA/CARMA2023/paper/view/16041 | es_ES |
dc.description.upvformatpinicio | 307 | es_ES |
dc.description.upvformatpfin | 317 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.relation.pasarela | OCS\16041 | es_ES |