计算机集成制造系统 ›› 2017, Vol. 23 ›› Issue (第11): 2371-2381.DOI: 10.13196/j.cims.2017.11.005

• 产品创新开发技术 • 上一篇    下一篇

制造业大数据联盟资源推送服务算法

翟丽丽1,2,沃强1,张树臣1,2   

  1. 1.哈尔滨理工大学管理学院
    2.哈尔滨理工大学高新技术产业发展研究中心
  • 出版日期:2017-11-30 发布日期:2017-11-30
  • 基金资助:
    国家自然科学基金资助项目(71672050,71774044,71272191);黑龙江省哲学社会科学研究规划资助项目(16GLB01);黑龙江省自然科学基金资助项目(F2017016);黑龙江省普通本科高等学校青年创新人才培养计划资助项目(UNPYSCT-2016038)。

Resource push service algorithm for big data alliance in manufacturing industry

  • Online:2017-11-30 Published:2017-11-30
  • Supported by:
    Project supported by the National Natural Science Foundation,China(No.71672050,71774044,71272191),the Philosophy and Social Sciences Research Planning Program of Heilongjiang Province,China(No.16GLB01),the Heilongjiang Provincial Natural Science Foundation,China(No.F2017016),and the University Nursing Program for Young Scholars with Creative Talents in Heilongjiang Province,China(No.UNPYSCT-2016038).

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摘要： 为了提高制造业大数据联盟资源共享效果及联盟成员的满意度,提出一种基于互信息特征权重和相似度的制造业大数据联盟资源推送算法。利用互信息特征权重和特征相似度分别对制造业大数据联盟成员评分和最近邻居产生的评分加以改进,从而提高资源推送质量。实验结果表明,该算法在一定程度上解决了制造业大数据联盟新成员资源推送和数据稀疏问题,有效提高了制造业大数据联盟成员满意度。

关键词: 制造业, 大数据联盟, 资源推送, 互信息, 推送算法

Abstract: To enhance the efficiency of data sharing and the satisfaction of big data alliance members in manufacturing industry,a resource pushing algorithm based on mutual information feature weight and similarity was proposed.To improve the quality of resource push,the scores of big data alliance members and the nearest neighbors were improved by using mutual information feature weight and feature similarity.The results showed that the algorithm could solve the problem of data push and data sparsity of alliance new members to a certain extent,and improve the satisfaction of big data alliance members effectively.

Key words: manufacturing industry, big data alliance, resource push, mutual information, push algorithm

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