Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Buddy tracking - efficient proximity detection among mobile friends
Pervasive and Mobile Computing
Efficient retrieval of the top-k most relevant spatial web objects
Proceedings of the VLDB Endowment
Efficient proximity detection among mobile users via self-tuning policies
Proceedings of the VLDB Endowment
Parallel main-memory indexing for moving-object query and update workloads
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
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Potential-Trust-Friends-Query is an important query in mobile social network, as it enables users to discover and interact with others happen to be in their physical vicinity. In our context, we attempt to find top-k mobile users for such query. We propose a novel trust scoring model that encompasses profile similarity, social closeness and interest similarity. Moveover, we devise a current-user-history-record (CUHR) index structure to support dynamic updates and efficient query processing. Based on CUHR index, we propose a query processing algorithm that exploits candidate generation-and-verification framework to answer queries. Extensive experiments was conducted on the real data set to illustrate the efficiency of our methods.