Conference Proceeding Article
The diffusion of social networks introduces new challengesand opportunities for advanced services, especially so with their ongoingaddition of location-based features. We show how applications like company andfriend recommendation could significantly benefit from incorporating social andspatial proximity, and study a query type that captures these twofold semantics.We develop highly scalable algorithms for its processing, and use real socialnetwork data to empirically verify their efficiency and efficacy.
Data structures, Distributed databases, Educational institutions, Euclidean distance, Indexes, Social network services
Databases and Information Systems
Data Management and Analytics
ICDE 2016: IEEE 32nd International Conference on Data Engineering: May 16-20, 2016, Helsinki, Finland: Proceedings
City or Country
MOURATIDIS, Kyriakos; LI, Jing; TANG, Yu; and MAMOULIS, Nikos..
Joint Search by Social and Spatial Proximity [Extended Abstract]. (2016). ICDE 2016: IEEE 32nd International Conference on Data Engineering: May 16-20, 2016, Helsinki, Finland: Proceedings. 1578-1579. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/3216
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