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Research on MapReduce-based Rocchio Relevance Feedback in Massive Information Filtering

机译:基于MapReduce的Rocchio相关反馈在大规模信息过滤中的研究

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Traditional text classification algorithms have vital impact on information filtering. However, their performances were confined to a large extent in terms of the massive data set. This paper proposes an approach using MapReduce-based Rocchio relevance feedback algorithm, which improved the traditional Rocchio algorithm in the MapReduce paradigm, to resolve the problem of massive information filtering. The experiments on Hadoop cluster showed an effective improvement in performance by using the new method.
机译:传统文本分类算法对信息滤波产生了至关重要的影响。但是,它们的性能在很大程度上在很大程度上局限于大规模数据集。本文提出了一种使用基于MapReduce的Rocchio相关反馈算法的方法,它在MapReduce范式中改进了传统的Rocchio算法,解决了大规模信息过滤问题。 Hadoop集群的实验通过使用新方法显示了性能的有效改善。

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