The GroupFinder framework addresses the new problem of recommending the best group of friends with whom to enjoy a given item, e.g., a travel destination or a movie. Given a user, her social network and a recommended item that is relevant for the user, our novel recommendation task tries to maximize: i) the relevance of the recommended item for every member of the group, and ii) the intra-group social relationships. This extended abstract shortly summarize the work in [4]: we introduce the User-Item Group Formation problem, the possible solutions and the recommendation framework that organizes them. We experiment the proposed solutions using four publicly available Location Based Social Network datasets confirming the effectiveness and the feasibility of the proposed solutions.
User-item group formation with GroupFinder
Nardini FM;Perego R;Renso C
2016
Abstract
The GroupFinder framework addresses the new problem of recommending the best group of friends with whom to enjoy a given item, e.g., a travel destination or a movie. Given a user, her social network and a recommended item that is relevant for the user, our novel recommendation task tries to maximize: i) the relevance of the recommended item for every member of the group, and ii) the intra-group social relationships. This extended abstract shortly summarize the work in [4]: we introduce the User-Item Group Formation problem, the possible solutions and the recommendation framework that organizes them. We experiment the proposed solutions using four publicly available Location Based Social Network datasets confirming the effectiveness and the feasibility of the proposed solutions.File | Dimensione | Formato | |
---|---|---|---|
prod_366938-doc_121241.pdf
accesso aperto
Descrizione: User-item group formation with GroupFinder
Tipologia:
Versione Editoriale (PDF)
Dimensione
742.12 kB
Formato
Adobe PDF
|
742.12 kB | Adobe PDF | Visualizza/Apri |
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.