Abstract
A location-aware publish/subscribe (pub/sub) system is gaining more and more interest in both industry and academia with the rapid progress of mobile Internet and the rising popularity of smart-phones. Nowadays, with the booming of E-commerce, OTO (online-to-offline) services are gaining more and more popularity, which results in millions of products with different structured descriptions and locations. To meet this requirement, a pub/sub system should handle subscriptions with location-aware boolean expressions to present users’ interests. In this paper, we propose an efficient location-aware pub/sub index for boolean expressions, called RP-trees. RP-trees integrates an R-tree index and a boolean expression index together, can efficiently and simultaneously prune boolean expressions and spatial dimensions. RP-trees is also extensible to support complex environment such as prefix-matching and subscriptions in format of CNF and DNF. Our experimental results show that RP-trees achieves good performance on a synthetic dataset and two real-world datasets (58 city and ebay).
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Acknowledgments
This work was partially supported by Chinese NSFC project (61402312, 61170020, 61402311, 61440053, 61572336), and the US National Science Foundation (IIS-1115417).
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Zhao, P., Jiang, H., Xu, J. et al. Location-aware publish/subscribe index with complex boolean expressions. World Wide Web 20, 1363–1384 (2017). https://doi.org/10.1007/s11280-017-0439-z
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DOI: https://doi.org/10.1007/s11280-017-0439-z