Recently, an ever increasing number of e-Commerce tools has been made available that are able to help customers by generating purposed recommendations. Many of them are centralized so that they have to face problems related to efficiency and scalability. A few of them are distributed, but in this case, the complexity of the e-Commerce process implies computation overhead on the client side, which is often unsuitable if mobile devices are used by customers. In this paper, we study how the software distribution in recommender systems affects their performances, depending on the characteristics of the e-Commerce population. To this end, we present a distributed testbed architecture for e-Commerce recommender systems using a multi-tiered agent-based approach to generate effective recommendations without requiring such an onerous amount of computation per single client. We use such a testbed to study the main advantages and limitations associated with the problem of distributing the computation of recommendations

A Distributed and Multi-Tiered Software Architecture for Assessing e-Commerce Recommendations

ROSACI D
;
SARNE' G
2016-01-01

Abstract

Recently, an ever increasing number of e-Commerce tools has been made available that are able to help customers by generating purposed recommendations. Many of them are centralized so that they have to face problems related to efficiency and scalability. A few of them are distributed, but in this case, the complexity of the e-Commerce process implies computation overhead on the client side, which is often unsuitable if mobile devices are used by customers. In this paper, we study how the software distribution in recommender systems affects their performances, depending on the characteristics of the e-Commerce population. To this end, we present a distributed testbed architecture for e-Commerce recommender systems using a multi-tiered agent-based approach to generate effective recommendations without requiring such an onerous amount of computation per single client. We use such a testbed to study the main advantages and limitations associated with the problem of distributing the computation of recommendations
2016
Multi-threading systems; Recommender Systems; Multi-Agent Systems
File in questo prodotto:
File Dimensione Formato  
palopoli_2016_CCPE_a_editor.pdf

non disponibili

Descrizione: versione editoriale
Tipologia: Versione Editoriale (PDF)
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 1.1 MB
Formato Adobe PDF
1.1 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
palopoli_2016_CCPE_a_post.pdf

Open Access dal 02/12/2020

Descrizione: versione postprint
Tipologia: Documento in Post-print
Licenza: Tutti i diritti riservati (All rights reserved)
Dimensione 1.46 MB
Formato Adobe PDF
1.46 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/20.500.12318/1692
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 9
  • ???jsp.display-item.citation.isi??? 6
social impact