大数据融合研究:问题与挑战  

Research on the Big Data Fusion:Issues and Challenges

作　　者：孟小峰[1] 杜治娟[1] 

机构地区：[1]中国人民大学信息学院,北京100872

出　　处：《计算机研究与发展》2016年第2期231-246,共16页Journal of Computer Research and Development

基　　金：国家自然科学基金项目(61532010;61379050;91224008);国家"八六三"高技术研究发展计划基金项目(2013AA013204);教育部高等学校博士学科点专项科研基金项目(20130004130001);中国人民大学科学研究基金项目(11XNL010)~~

摘　　要：随着大规模数据的关联和交叉,数据特征和现实需求都发生了变化.以大规模、多源异构、跨领域、跨媒体、跨语言、动态演化、普适化为主要特征的数据发挥着更重要的作用,相应的数据存储、分析和理解也面临着重大挑战.当下亟待解决的问题是如何利用数据的关联、交叉和融合实现大数据的价值最大化.认为解决这一问题的关键在于数据的融合,所以提出了大数据融合的概念.首先以Web数据、科学数据和商业数据的融合作为案例分析了大数据融合的需求和必要性,并提出了大数据融合的新任务;然后,总结分析了现有融合技术;最后针对大数据融合问题可能面临的挑战和大数据融合带来的问题进行了分析.Data characteristics and realistic demands have changed because of the large-scale data’s links and crossover. The data, which has main features of large scale, multi-source heterogeneous, cross domain, cross media, cross language, dynamic evolution and generalization, is playing an important role. And the corresponding data storage, analysis and understanding are also facing a major challenge. The immediate problem to be solved is how to use the data association, cross and integration to achieve the maximization of the value of big data. Our paper believes that the key to solve this problem lies in the integration of data, so we put forward the concept of large data fusion. We use Web data, scientific data and business data fusion as a case to analyze the demand and necessity of data fusion, and propose a new task of large data fusion, but also summarize and analyze the existing fusion technologies. Finally, we analyze the challenges that may be faced in the process of large data fusion and the problems caused by large data fusion.

关 键 词：大数据 数据集成 数据融合 知识融合 数据管理 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]