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Finding patterns from a user-centric perspective using knowledge discovery methods

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Finding patterns from a user-centric perspective using knowledge discovery methods

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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


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