unibo

PhD course - Designing Distributed Geospatial Data-Intensive Applications
PhD course 2022
Jul 18, 2022
ApproxSSPS
ApproxSSPS is a system that aims at maintaining the stability of distributed geospatial data processing systems during peak data arrival rates, with quality-of-service guarantees.
Code
ApproxSSPS
SpatialSPE
SpatialSPE is an approximate query processing engine for fast-arriving geospatial data streams. It aims at maintaining the QoS during high-peak data streaming loads.
Code
SpatialSPE
MeteoMobil
MeteoMobil is an interactive system for the combined analytics of integrated information representing mobility and environment conditions
Code
MeteoMobil
Efficiently Integrating Mobility and Environment Data for Climate Change Analytics
summary
Isam Mashhour Al Jawarneh, Paolo Bellavista, Antonio Corradi, Luca Foschini, Rebecca Montanari
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Context Incorporation Techniques for Social Recommender Systems
summary
Isam Mashhour Al Jawarneh, Paolo Bellavista, Antonio Corradi, Luca Foschini, Rebecca Montanari
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CA-NCF
CA-NCF is a Pre-Filtering Approach for Incorporating Contextual Information Into Deep Learning Based Recommender Systems
Code
CA-NCF
US-NCF
US-NCF is a multi-domain deep-learning based context-aware recommender system
Code
US-NCF
QoS-Aware Approximate Query Processing for Smart Cities Spatial Data Streams
summary
Isam Mashhour Al Jawarneh, Paolo Bellavista, Antonio Corradi, Luca Foschini, Rebecca Montanari
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Locality-Preserving Spatial Partitioning for Geo Big Data Analytics in Main Memory Frameworks
summary
Isam Mashhour Al Jawarneh, Paolo Bellavista, Antonio Corradi, Luca Foschini, Rebecca Montanari
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