Publication Type

Conference Proceeding Article

Publication Date

5-2016

Abstract

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.

Keywords

Data structures, Distributed databases, Educational institutions, Euclidean distance, Indexes, Social network services

Discipline

Databases and Information Systems

Research Areas

Data Management and Analytics

Publication

ICDE 2016: IEEE 32nd International Conference on Data Engineering: May 16-20, 2016, Helsinki, Finland: Proceedings

First Page

1578

Last Page

1579

ISBN

9781509020201

Identifier

10.1109/ICDE.2016.7498434

Publisher

IEEE

City or Country

Piscataway, NJ

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://dx.doi.org/10.1109/ICDE.2016.7498434

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