In this paper we present I-MALL, an ICT hardware and software infrastructure that enables the management of services related to places such as shopping malls, showrooms, and conferences held in dedicated facilities. I-MALL offers a network of services that perform customer behavior analysis through computer vision and provide personalized recommendations made available on digital signage terminals. The user can also interact with a social robot. Recommendations are inferred on the basis of the profile of interests computed by the system analysing the history of the customer visit and his/her behavior including information from his/her appearance, the route taken inside the facility, as well as his/her mood and gaze.

Becattini F., Becchi G., Ferracani A., Bimbo A.D., Lo Presti Liliana, Mazzola G., et al. (2022). I-MALL An Effective Framework for Personalized Visits. Improving the Customer Experience in Stores. In MCFR 2022 - Proceedings of the 1st Workshop on Multimedia Computing towards Fashion Recommendation (pp. 11-19). Association for Computing Machinery, Inc [10.1145/3552468.3555365].

I-MALL An Effective Framework for Personalized Visits. Improving the Customer Experience in Stores

Lo Presti Liliana;Mazzola G.;La Cascia M.;
2022-10-10

Abstract

In this paper we present I-MALL, an ICT hardware and software infrastructure that enables the management of services related to places such as shopping malls, showrooms, and conferences held in dedicated facilities. I-MALL offers a network of services that perform customer behavior analysis through computer vision and provide personalized recommendations made available on digital signage terminals. The user can also interact with a social robot. Recommendations are inferred on the basis of the profile of interests computed by the system analysing the history of the customer visit and his/her behavior including information from his/her appearance, the route taken inside the facility, as well as his/her mood and gaze.
10-ott-2022
Settore ING-INF/05 - Sistemi Di Elaborazione Delle Informazioni
9781450394987
Becattini F., Becchi G., Ferracani A., Bimbo A.D., Lo Presti Liliana, Mazzola G., et al. (2022). I-MALL An Effective Framework for Personalized Visits. Improving the Customer Experience in Stores. In MCFR 2022 - Proceedings of the 1st Workshop on Multimedia Computing towards Fashion Recommendation (pp. 11-19). Association for Computing Machinery, Inc [10.1145/3552468.3555365].
File in questo prodotto:
File Dimensione Formato  
IMALL_ACMMMW.pdf

accesso aperto

Descrizione: Articolo
Tipologia: Versione Editoriale
Dimensione 2.86 MB
Formato Adobe PDF
2.86 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/591360
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? ND
social impact