Heterogeneous Knowledge Fusion Algorithm for Minority Cultural Resources based on MapReduce

Heterogeneous Knowledge Fusion Algorithm for Minority Cultural Resources based on MapReduce
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基于MapReduce的少数民族文化资源异质知识融合算法

DOI:
10.23940/ijpe.19.08.p26.22582266
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发表时间:
2019-08
影响因子:
--
通讯作者:
Gan Jianhou
Gan Jianhou
中科院分区:
--
文献类型:
--
作者:
Liu Ying;Zhou Juxiang;Gan Jianhou

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针对当前知识融合方法的不足以及对大数据环境下知识融合算法的理解,提出一种基于MapReduce的少数民族文化资源异构知识融合算法。为了提高融合算法的性能,将该算法用于相似度计算。它是在传统的属性相似度计算方法的基础上进行改进的。基于Hadoop平台和MapReduce框架,对实验平台进行了验证。实验结果表明,所提出的基于MapReduce的民族文化资源异构知识融合算法无论在准确性还是有效性上都是有效可行的
Aiming at the shortcomings of current knowledge fusion methods and understanding the knowledge fusion algorithm in the big data environment, this paper proposes a heterogeneous knowledge fusion algorithm based on MapReduce for minority cultural resources. In order to improve the performance of the fusion algorithm, the algorithm is used in the similarity calculation. It is improved on the basis of the traditional attribute similarity calculation method. Based on the Hadoop platform and MapReduce framework, the experimental platform is validated. The experimental results show that the proposed MapReduce-based heterogeneous knowledge fusion algorithm for ethnic cultural resources is effective and feasible, both in terms of accuracy and effectiveness
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