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Durable queries over non-synchronized temporal data

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Abstract

Temporal data are ubiquitous nowadays and efficient management of temporal data is of key importance. A temporal data typically describes the evolution of an object over time. One of the most useful queries over temporal data are the durable top-k queries. Given a time window, a durable top-k query finds the objects that are frequently among the best. Existing solutions to durable top-k queries assume that all temporal data are sampled at the same time points (i.e., at any time, there is a corresponding observed value for every temporal data). However, in many practical applications, temporal data are collected from multiple data sources with different sampling rates. In this light, we investigate the efficient processing of durable top-k queries over temporal data with different sampling rates. We propose an efficient sweep line algorithm to process durable top-k queries over non-synchronized temporal data. We conduct extensive experiments on two real datasets to test the performance of our proposed method. The results show that our methods outperforms the baseline solutions by a large margin.

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Notes

  1. https://www.kaggle.com/datasets/paultimothymooney/stock-market-data

  2. https://snap.stanford.edu/data/loc-gowalla.html

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Acknowledgements

The authors would like to thank the Science and Technology Department of Fujian Province, China, for its financial support to this work.

Funding

The work is supported by the Fujian Province Science and Technology Plan Project (No. 2019J05123).

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Authors and Affiliations

  1. School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, China

    Yanqi Xie, Wei Weng & Jianmin Li

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  1. Yanqi Xie
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  2. Wei Weng
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Contributions

The authors’ contributions are as follows.

– Yanqi Xie: Problem formulation, algorithm design, coding, and paper writing.

– Wei Weng: Problem formulation, algorithm analysis, and experiment analysis.

– Jianmin Li: Problem formulation, algorithm design, algorithm analysis, and paper proofreading.

All authors have reviewed the manuscript.

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Correspondence to Jianmin Li.

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Xie, Y., Weng, W. & Li, J. Durable queries over non-synchronized temporal data. World Wide Web 26, 2099–2113 (2023). https://doi.org/10.1007/s11280-022-01122-2

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