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GL-RF: a reconciliation framework for label-free entity resolution

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Acknowledgements

We thank Murtadha Ahmed, Yiyi Li, Ping Zhong, YanyanWang, and Jing Su for their invaluable suggestions. This work was supported by the Ministry of Science and Technology of China, National Key Research and Development Program (2016YFB1000703), and the National Natural Science Foundation of China (Grant Nos. 61732014, 61332006, 61472321, 61502390, and 61672432).

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Authors and Affiliations

  1. School of Computer Science and Engineering, Northwestern Polytechnical University, Xi’an, 710072, China

    Yaoli Xu, Zhanhuai Li, Qun Chen & Fengfeng Fan

  2. Key Laboratory of Big Data Storage and Management, Northwestern Polytechnical University, Ministry of Industry and Information Technology, Xi’an, 710129, China

    Yaoli Xu, Zhanhuai Li, Qun Chen & Fengfeng Fan

Authors
  1. Yaoli Xu
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  2. Zhanhuai Li
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  3. Qun Chen
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  4. Fengfeng Fan
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Correspondence to Qun Chen.

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Xu, Y., Li, Z., Chen, Q. et al. GL-RF: a reconciliation framework for label-free entity resolution. Front. Comput. Sci. 12, 1035–1037 (2018). https://doi.org/10.1007/s11704-018-7285-8

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  • DOI: https://doi.org/10.1007/s11704-018-7285-8

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