Joint Search by Social and Spatial Proximity [Extended Abstract]

• Main Authors: MOURATIDIS, Kyriakos, LI, Jing, TANG, Yu, MAMOULIS, Nikos
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2016
• Subjects: Data structures; Distributed databases; Educational institutions; Euclidean distance; Indexes; Social network services; Databases and Information Systems; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/3216; https://ink.library.smu.edu.sg/context/sis_research/article/4218/viewcontent/8390110.pdf
• Institution: Singapore Management University

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.