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http://dx.doi.org/10.3837/tiis.2018.12.015

EFTG: Efficient and Flexible Top-K Geo-textual Publish/Subscribe  

zhu, Hong (School of Computer Science and Technology, Huazhong University of Science and Technology)
Li, Hongbo (School of Computer Science and Technology, Huazhong University of Science and Technology)
Cui, Zongmin (School of Information Science and Technology, Jiujiang University)
Cao, Zhongsheng (School of Computer Science and Technology, Huazhong University of Science and Technology)
Xie, Meiyi (School of Computer Science and Technology, Huazhong University of Science and Technology)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.12, no.12, 2018 , pp. 5877-5897 More about this Journal
Abstract
With the popularity of mobile networks and smartphones, geo-textual publish/subscribe messaging has attracted wide attention. Different from the traditional publish/subscribe format, geo-textual data is published and subscribed in the form of dynamic data flow in the mobile network. The difference creates more requirements for efficiency and flexibility. However, most of the existing Top-k geo-textual publish/subscribe schemes have the following deficiencies: (1) All publications have to be scored for each subscription, which is not efficient enough. (2) A user should take time to set a threshold for each subscription, which is not flexible enough. Therefore, we propose an efficient and flexible Top-k geo-textual publish/subscribe scheme. First, our scheme groups publish and subscribe based on text classification. Thus, only a few parts of related publications should be scored for each subscription, which significantly enhances efficiency. Second, our scheme proposes an adaptive publish/subscribe matching algorithm. The algorithm does not require the user to set a threshold. It can adaptively return Top-k results to the user for each subscription, which significantly enhances flexibility. Finally, theoretical analysis and experimental evaluation verify the efficiency and effectiveness of our scheme.
Keywords
Top-k; geo-textual; publish/subscribe; efficient and flexible; text classification;
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