Page 192 - 《软件学报》2021年第9期

软件学报 ISSN 1000-9825, CODEN RUXUEW E-mail: jos@iscas.ac.cn
Journal of Software,2021,32(9):2816−2836 [doi: 10.13328/j.cnki.jos.006010] http://www.jos.org.cn
©中国科学院软件研究所版权所有. Tel: +86-10-62562563

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碎片化家谱数据的融合技术

5
吴信东 1,2,3,4 , 李 娇 1,2,3 , 周 鹏 , 卜晨阳 1,2,3
1
(大数据知识工程教育部重点实验室(合肥工业大学),安徽 合肥 230009)
2 (合肥工业大学 计算机与信息学院,安徽 合肥 230601)
3 (合肥工业大学 大知识科学研究院,安徽 合肥 230009)
4
(明略科技集团,北京 100102)
5
(安徽大学 计算机科学与技术学院,安徽 合肥 230601)
通讯作者: 吴信东, E-mail: xwu@hfut.edu.cn

摘 要: 家谱数据是典型的碎片化数据,具有海量、多源、异构、自治的特点.通过数据融合技术将互联网中零散
分布的家谱数据融合成一个全面、准确的家谱数据库,有利于针对家谱数据进行知识挖掘和推理,从而为用户提供
姓氏起源、姓氏变迁和姓氏间关联等隐含信息.在大数据知识工程 BigKE 模型的基础上,提出了一个结合 HAO 智
能模型的碎片化数据融合框架 FDF-HAO(fragmented data fusion with human intelligence, artificial intelligence and
organizational intelligence),阐述了架构中每层的作用、关键技术和需要解决的问题,并以家谱数据为例,验证了该数
据融合框架的有效性.最后,对碎片化数据融合的前景进行展望.
关键词: 碎片化数据;数据融合;家谱数据;多源异构;HAO 智能模型
中图法分类号: TP311

中文引用格式: 吴信东,李娇,周鹏,卜晨阳.碎片化家谱数据的融合技术.软件学报,2021,32(9):2816−2836. http://www.jos.org.
cn/1000-9825/6010.htm
英文引用格式: Wu XD, Li J, Zhou P, Bu CY. Fusion technique for fragmented genealogy data. Ruan Jian Xue Bao/Journal of
Software, 2021,32(9):2816−2836 (in Chinese). http://www.jos.org.cn/1000-9825/6010.htm
Fusion Technique for Fragmented Genealogy Data

5
WU Xin-Dong 1,2,3,4 , LI Jiao 1,2,3 , ZHOU Peng , BU Chen-Yang 1,2,3
1
(Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology), Hefei 230009, China)
2
(School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230601, China)
3
(Research Institute of Big Knowledge, Hefei University of Technology, Hefei 230009, China)
4
(Mininglamp Technology, Beijing 100102, China)
5
(School of Computer Science and Technology, Anhui University, Hefei 230601, China)
Abstract: Genealogy data is a typical example for data fragmentation with massive, multiple, heterogeneous, and autonomous sources.
Merging scattered genealogy data on the Internet into a comprehensive and accurate genealogy database through data fusion technologies,
can be beneficial to knowledge mining and reasoning from genealogy data, and can provide users with implicit information such as
surname origins, surname changes, and surname associations. Based on BigKE, a big data knowledge engineering model for big
knowledge, this study proposes an FDF-HAO framework (fragmented data fusion with human intelligence, artificial intelligence, and
organizational intelligence), describes the functionalities, key technologies, and problems to be solved of each layer in the framework, and

∗ 基金项目: 国家重点研发计划(2016YFB1000901); 国家自然科学基金(91746209); 教育部创新团队项目(IRT17R3)
Foundation item: National Key Researh and Development Program of China (2016YFB1000901); National Natural Science
Foundation of China (91746209); Program for Changjiang Scholars and Innovative Research Team in University (PCSIRT) of the
Ministry of Education (IRT17R3)
收稿时间: 2019-06-22; 修改时间: 2019-09-20, 2019-11-19; 采用时间: 2020-01-02; jos 在线出版时间: 2020-04-21