Interest detection; Behaviour modelling; High utility events
Résumé :
[en] Mobile applications became the main interaction channel in several domains, such as banking. Consequently, understanding user behaviour on those apps has drawn attention in order to extract business-oriented outcomes. By combining Markov Chain and graph theory techniques, we successfully developed a process to model the app, to extract the click high utility events, to score the interest on those events and cluster the groups of interest. We tested our approach on an European bank dataset with over 3.5 millions of user's session. By implementing our approach, analysts can gain knowledge of user behaviour in terms of events that are important to the domain.
Disciplines :
Sciences informatiques
Auteur, co-auteur :
Ota, Fernando Kaway Carvalho
DAMOUN, Farouk ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SEDAN
Lagraa, Sofiane
Becerra-Sanchez, Patricia
HILGER, Jean ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SnT Finnovation Hub
STATE, Radu ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > SEDAN
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
Event-Driven Interest Detection for Task-Oriented Mobile Apps
Date de publication/diffusion :
2022
Nom de la manifestation :
18th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services
Lieu de la manifestation :
Beppu, Japon
Date de la manifestation :
November 8-11, 2021
Sur invitation :
Oui
Manifestation à portée :
International
Titre de l'ouvrage principal :
Mobile and Ubiquitous Systems: Computing, Networking and Services
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