计算机科学 ›› 2020, Vol. 47 ›› Issue (11): 113-121.doi: 10.11896/jsjkx.191000071

• 数据库&大数据&数据科学 • 上一篇    下一篇

大数据智能检索与大数据区块元智能分离

郝秀梅1, 史开泉2   

  1. 1 山东财经大学数学与数量经济学院 济南 250014
    2 山东大学数学学院 济南 250100
  • 收稿日期:2019-10-12 修回日期:2020-03-27 出版日期:2020-11-15 发布日期:2020-11-05
  • 通讯作者: 史开泉(shikq@sdu.edu.cn)
  • 作者简介:hxm0912@126.com
  • 基金资助:
    国家社会科学基金项目(71663010);山东省自然科学基金项目(zr2013aq019)

Big Data Intelligent Retrieval and Big Data Block Element Intelligence Separation

HAO Xiu-mei1, SHI Kai-quan2   

  1. 1 School of Mathematics and Quantitative Economics,Shandong University of Finance and Economics,Jinan 250014,China
    2 School of Mathematics,Shandong University,Jinan 250100,China
  • Received:2019-10-12 Revised:2020-03-27 Online:2020-11-15 Published:2020-11-05
  • About author:HAO Xiu-mei,born in 1965,Ph.D,professor,Ph.D supervisor.Her main research interests include risk data identification,big data analysis and application and rough system theory and app-lication.
    SHI Kai-quan,born in 1945,professor,Ph.Dsupervisor.His main research interests include big data theory and application,information intelligent system.He proposed S-rough sets,function S-rough sets,P-sets,inverse P-sets,function P-sets and function inverse P-sets.More papers were published in Science in China E,Science in China F and other journals. In 2010-2016,a number of papers were selected as “100 most influential domestic academic papers in China”.The two papers published in Computer Science,“Function S-rough sets,function rough sets and separation-composition of law for information systems” and “P-sets,inverse P-sets and the intelligent fusion-filter identification of information”were listed among them.A number of papers were selected in Frontrunner 5000.A number of monographs have been published.
  • Supported by:
    This work was supported by the National Social Science Foundation of China (71663010) and Natural Science Foundation of Shandong Province,China (zr2013aq019).

摘要: 文中利用逆P-集合生成∨型大数据结构,给出∨型大数据的新概念,如大数据区块、区块矩阵、区块元、区块元矩阵与数据元概念;利用这些概念给出区块属性推理结构、区块矩阵推理结构、区块元智能分离定理、区块元智能检索定理、区块与区块元等价类定理;给出区块元智能分离准则、区块智能检索准则;给出区块元智能分离-区块智能检索算法与算法过程;给出大数据智能检索-大数据区块元智能分离-获取的应用。∨型大数据满足“属性析取”的逻辑特征。

关键词: ∨型大数据, 大数据区块, 应用, 智能检索算法, 智能检索准则, 属性-矩阵推理

Abstract: By using∨-type big data structure generated by inverse P-sets,some new concepts of ∨-type big data are given,such as big data block,block matrix,block element,block element matrix and data element.Based on these concepts,the reasoning structure of block attribute,the reasoning structure of block matrix,the intelligent separation theorems,the intelligent retrieval theorems of block element and the equivalence class theorems of block and block element are given.An intelligent separation criterion of block element and an intelligent retrieval criterion of block are presented.A block element intelligent separation-block intelligent retrieval algorithm and its algorithm process are given.The application of big data intelligent retrieval-big data block element intelligent separation-acquisition is given.∨-type big data satisfies the logical characteristic of ‘attribute disjunction'.

Key words: Application, Attribute-matrix reasoning, Big data block, Intelligent retrieval algorithm, Intelligent retrieval criterion, V-type big data

中图分类号: 

  • O144
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