Abstract
With the popularity of social media and GPS equipment, a large number of the location-text data have been produced in the form of stream. The popularity leads to a variety of applications, such as based-location advice and location information transmission. Existing top-k location-text publish/subscribe schemes need subscriber to set a threshold, k value (the number of returned top results) and preference parameter \( \delta \) (the decision of which one is more important about location or text). The threshold brings lots of disadvantages to subscribers and publishers. Therefore in this paper, we propose an efficient top-k location-text publish/subscribe scheme without threshold which is named as TGT. Our scheme only needs subscriber to input k value and preference parameter \( \delta \). Then TGT returns top-k results to the subscriber based on k and \( \delta \) without any threshold. Therefore, our scheme can reduce redundant computation, improve the recall ratio and facilitate the subscriber. Extensive experiments prove the efficiency and effectiveness of the proposed scheme.
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Acknowledgment
This research was supported by the National Natural Science Foundation of China [Nos. 61772215 and 61762055]; and the Jiangxi Provincial Natural Science Foundation of China [No. 20161BAB202036].
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Zhu, H., Li, H., Cui, Z., Cao, Z., Xie, M. (2018). Convenient Top-k Location-Text Publish/Subscribe Scheme. In: Li, K., Li, W., Chen, Z., Liu, Y. (eds) Computational Intelligence and Intelligent Systems. ISICA 2017. Communications in Computer and Information Science, vol 874. Springer, Singapore. https://doi.org/10.1007/978-981-13-1651-7_16
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DOI: https://doi.org/10.1007/978-981-13-1651-7_16
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