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Reply to comment on 'WebPIE: A Web-scale parallel inference engine using MapReduce'

机译:对“ WebPIE:使用MapReduce的Web规模并行推理引擎”的评论回复

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Thank you for having shared with us this letter. We are always keen to discuss any unclear points and any limitations of our work, and we thank Dr. Patel-Schneider for his letter. The letter that we received can be divided in two parts. The first part addresses points which, as the letter states, "can be overcome without changing the thrust of the paper". This leads us to a corrigendum with clarifications and bug fixes in the original paper. Although these are valuable improvements, none of these invalidate our approach or our evaluation. The second part of the letter addresses "the deep question whether the general approach in the paper can actually perform scalable RDFS materialization". By addressing the four points below, we conclude that fortunately the answer to this question is yes.
机译:感谢您与我们分享这封信。我们始终热衷于讨论我们工作中的任何不清楚之处和局限性,我们感谢Patel-Schneider博士的来信。我们收到的信可以分为两部分。第一部分论述了这些点,正如字母所指出的,“可以在不改变纸张推力的情况下克服”。这导致我们在原始论文中进行了更正并更正了一些错误。尽管这些都是有价值的改进,但是这些都不会使我们的方法或评估无效。这封信的第二部分解决了“深入的问题,即本文中的一般方法是否可以实际执行可伸缩的RDFS实现”。通过解决以下四点,我们得出结论,幸运的是,这个问题的答案是肯定的。

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  • 来源
    《Journal of web semantics:》 |2012年第9期|71-72|共2页
  • 作者单位

    Department of Computer Science, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, Netherlands;

    IBM Research Ireland, IBM Technology Campus, Damastown Industrial Estate, Dublin 15, Ireland;

    Department of Computer Science, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, Netherlands;

    Department of Computer Science, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, Netherlands;

    Department of Computer Science, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, Netherlands;

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