A Personalized Recommender System for Pervasive Social Networks

Abstract

The current availability of interconnected portable devices, and the advent of the Web 2.0, raise the problem of supporting anywhere and anytime access to a huge amount of content, generated and shared by mobile users. In this work we propose a novel framework for pervasive social networks, called Pervasive PLIERS (pPLIERS), able to discover and select, in a highly personalized way, contents of interest for single mobile users. pPLIERS exploits the recently proposed PLIERS tag based recommender system as context a reasoning tool able to adapt recommendations to heterogeneous interest profiles of different users. pPLIERS effectively operates also when limited knowledge about the network is maintained. It is implemented in a completely decentralized environment, in which new contents are continuously generated and diffused through the network, and it relies only on the exchange of single nodes knowledge during proximity contacts and through device to device communications. We evaluated pPLIERS by simulating its behaviour in three different scenarios: a big event (Expo 2015), a conference venue (ACM KDD 2015), and a working day in the city of Helsinki. For each scenario, we used real or synthetic mobility traces and we extracted real datasets from Twitter interactions to characterise the generation and sharing of user contents.

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Cited by in corpus (7)

• Recommender Systems for Online and Mobile Social Networks: A survey
• The Structure of Online Social Networks Mirror Those in the Offline World
• The Internet of People: A human and data-centric paradigm for the Next Generation Internet
• Context-Aware Configuration and Management of WiFi Direct Groups for Real Opportunistic Networks
• On-device modeling of user's social context and familiar places from smartphone-embedded sensor data
• Lightweight Modeling of User Context Combining Physical and Virtual Sensor Data
• MyDigitalFootprint: an extensive context dataset for pervasive computing applications at the edge