Abstract
Nowadays, massive geo-tagged records are generated on the social media. These records are useful when the users intend to plan a trip and are interested in some specific topics along the trip. With such redundant records, a publish/subscribe system has been designed to allow the users who are interested in certain information (i.e., the subscribers) to receive messages from some message generators (i.e., the publishers). Existing efforts on publish/subscribe mainly focus on the textual content or the spatial location of the subscribers, while leaving the consideration of incorporating the subscribers’ moving behaviors and temporal information. Therefore, in this paper, we propose a Time-aware Path-based Publish/Subscribe (TPPS) model, where we propose a filtering-verification framework that contains two kinds of filters, i.e., time-aware location-based filter and time-aware region-based filter, with considering both temporal information and moving behaviors, and filtering unrelated subscriptions for each message. We evaluate the efficiency of our approach on a real-world dataset and the experimental results demonstrate the superiority of our method in both efficiency and effectiveness.
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This research is partially supported by the Natural Science Foundation of China (Grant No. 61502324, 61532018).
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Jia, M., Zhao, Y., Zheng, B., Liu, G., Zheng, K. (2018). A Time-Aware Path-Based Publish/Subscribe Framework. In: Pei, J., Manolopoulos, Y., Sadiq, S., Li, J. (eds) Database Systems for Advanced Applications. DASFAA 2018. Lecture Notes in Computer Science(), vol 10827. Springer, Cham. https://doi.org/10.1007/978-3-319-91452-7_33
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