Pubblicazioni

Autori:

DALLA VECCHIA, Anna; Migliorini, Sara; Quintarelli, Elisa; Belussi, Alberto

Titolo:

A Context-Aware Recommendation System with a Crowding Forecaster

Anno:

2023

Tipologia prodotto:

Contributo in atti di convegno

Tipologia ANVUR:

Contributo in Atti di convegno

Lingua:

Inglese

Formato:

Elettronico

Nome rivista:

CEUR WORKSHOP PROCEEDINGS

ISSN Rivista:

1613-0073

N° Volume:

3478

Titolo del Convegno:

31st Symposium of Advanced Database Systems (SEBD 2023)

Luogo:

Galzingano Terme, Italy

Periodo:

July 2nd to 5th, 2023

Editore:

CEUR-WS.org

Casa editrice:

CEUR-WS.org

Intervallo pagine:

632-640

Parole chiave:

Recommendation systems; Crowding forecasting; Deep learning

Breve descrizione dei contenuti:

Recommendation systems (RSs) are increasing their popularity in recent years. Many big IT companies like Google, Amazon and Netflix, have a RS at the core of their business. In this paper, we propose a modular platform for enhancing a RS for the tourism domain with a crowding forecaster, which is able to produce an estimation about the current and future occupation of different Points of Interest (PoIs) by taking into consideration also contextual aspects. The main advantage of the proposed system is its modularity and the ability to be easily tailored to different application domains. Moreover, the use of standard and pluggable components allows the system to be integrated in different application scenarios.

Id prodotto:

135216

Handle IRIS:

11562/1104926

ultima modifica:

27 ottobre 2023

Citazione bibliografica:

DALLA VECCHIA, Anna; Migliorini, Sara; Quintarelli, Elisa; Belussi, Alberto, A Context-Aware Recommendation System with a Crowding Forecaster in «CEUR WORKSHOP PROCEEDINGS» vol. 3478 CEUR-WS.org  in Proceedings of the 31st Symposium of Advanced Database Systems , CEUR-WS.org , Atti di "31st Symposium of Advanced Database Systems (SEBD 2023)" , Galzingano Terme, Italy , July 2nd to 5th, 2023 , 2023 , pp. 632-640

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