图书情报工作 ›› 2015, Vol. 59 ›› Issue (16): 5-10.DOI: 10.13266/j.issn.0252-3116.2015.16.001

• 理论研究 • 上一篇    下一篇

大数据环境下多源信息融合的理论与应用探讨

化柏林, 李广建   

  1. 北京大学信息管理系 北京 100871
  • 收稿日期:2015-07-13 修回日期:2015-08-04 出版日期:2015-08-20 发布日期:2015-08-20
  • 作者简介:化柏林(ORCID:0000-0001-9248-6455),博士后,E-mail:huabolin@pku.edu.cn;李广建(ORCID:0000-0002-2897-6246),教授,博士生导师。
  • 基金资助:
    本文系中国博士后科学基金特别资助项目“大数据环境下的多源信息融合机理与方法研究”(项目编号:2015T80027)和国家社会科学基金重点项目“大数据环境下的计算型情报分析方法与技术研究”(项目编号:14ATQ005)研究成果之一。

Discussion on Theory and Application of Multi-Source Information Fusion in Big Data Environment

Hua Bolin, Li Guangjian   

  1. Department of Information Management, Peking University, Beijing 100871
  • Received:2015-07-13 Revised:2015-08-04 Online:2015-08-20 Published:2015-08-20

摘要: [目的/意义]从理论、方法、技术与应用的视角研究大数据环境下的多源信息融合问题。[方法/过程]探索多源信息融合的理论基础与科学依据,梳理多源信息融合的问题与现象,对多源信息融合的技术与方法进行归纳总结,对构建大数据环境下的多源信息融合应用进行探讨。[结果/结论]大数据环境下的多源信息融合理论包括相关性原理、多元表示原理、意义建构理论等,多源信息融合方法包括统一标识、数据比对、异构加权等一系列过程以及多种分析建模方法,多源信息融合在国家层面、城市或行业组织层面、企业机构层面都有着广泛的需求与应用。

关键词: 大数据, 多源信息融, 情报分析

Abstract: [Purpose/significance]To study the problem of multi-source information fusion in big data environment from the perspective of theory, method, technology and application.[Method/process]Explores the theory foundation and scientific basis of multi-source information fusion, and clarifies the problems and phenomenon of the multi-source information fusion, then summarizes technologies and methods of multi-source information fusion, to present applications of multi-source information fusion in big data environment.[Result/conclusion]Theories of multi-source information fusion include relevance principle, polyrepresentation principle, and sense-making theory.Methods of multi-source information fusion include a series of processes, such as unified resource, data comparison, heterogeneous weighted and a variety of analysis and modeling methods.At last, widely application and demand of multi-source information fusion are presented at the national level, city or level of industry, enterprise organization level.

Key words: big data, multi-source information fusion, intelligence analysis

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