Applications and services that take advantage of social data usually infer social relationships using information produced only within their own context, using a greatly simplified representation of users' social data. We propose to combine social information from multiple sources into a directed and weighted social multigraph in order to enable novel socially-aware applications and services. We present GeoS, a geo-social data management service which implements a representative set of social inferences and can run on a decentralized system. We demonstrate GeoS' potential for social applications on a collection of social data that combines collocation information and Facebook friendship declarations from 100 students. We demonstrate its performance by testing it both on PlanetLab and a LAN with a realistic workload for a 1000 node graph.
| Identifer | oai:union.ndltd.org:USF/oai:scholarcommons.usf.edu:etd-2560 |
| Date | 18 May 2010 |
| Creators | Anderson, Paul |
| Publisher | Scholar Commons |
| Source Sets | University of South Flordia |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Graduate Theses and Dissertations |
| Rights | default |
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