Title :
Joint Search by Social and Spatial Proximity
Author :
Mouratidis, Kyriakos ; Jing Li ; Yu Tang ; Mamoulis, Nikos
Author_Institution :
Sch. of Inf. Syst., Singapore Manage. Univ., Singapore, Singapore
Abstract :
The diffusion of social networks introduces new challenges and opportunities for advanced services, especially so with their ongoing addition of location-based features. We show how applications like company and friend recommendation could significantly benefit from incorporating social and spatial proximity, and study a query type that captures these two-fold semantics. We develop highly scalable algorithms for its processing, and enhance them with elaborate optimizations. Finally, we use real social network data to empirically verify the efficiency and efficacy of our solutions.
Keywords :
query processing; recommender systems; social networking (online); social sciences computing; friend recommendation; joint search; location-based features; query type; social networks diffusion; social proximity; spatial proximity; top-k search; two-fold semantics; Data structures; Distributed databases; Educational institutions; Euclidean distance; Indexes; Social network services; Tin; Location-based social networks; friend recommendation; top-k search in multiple domains;
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
DOI :
10.1109/TKDE.2014.2339838