| 碎片化家谱数据的融合技术 |
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| 引用本文： | 吴信东,李娇,周鹏,卜晨阳.碎片化家谱数据的融合技术[J].软件学报,2021,32(9):2816-2836. |
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| 作者姓名： | 吴信东 李娇 周鹏 卜晨阳 |
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| 作者单位： | 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;合肥工业大学 计算机与信息学院, 安徽 合肥 230601;合肥工业大学 大知识科学研究院, 安徽 合肥 230009;明略科技集团, 北京 100102;安徽大学计算机科学与技术学院, 安徽 合肥 230601 |
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| 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） |
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| 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.
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| 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 |
| 收稿时间： | 2019/6/22 0:00:00 |
| 修稿时间： | 2019/11/19 0:00:00 |
Fusion Technique for Fragmented Genealogy Data |
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| WU Xin-Dong,LI Jiao,ZHOU Peng,BU Chen-Yang.Fusion Technique for Fragmented Genealogy Data[J].Journal of Software,2021,32(9):2816-2836. |
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| Authors: | WU Xin-Dong LI Jiao ZHOU Peng BU Chen-Yang |
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| Affiliation: | Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology), Hefei 230009, China;School of Computer Science and Information Engineering, Hefei University of Technology, Hefei 230601, China;Research Institute of Big Knowledge, Hefei University of Technology, Hefei 230009, China;Mininglamp Technology, Beijing 100102, China;School of Computer Science and Technology, Anhui University, Hefei 230601, China |
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| 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 verifies the validity of the data fusion framework by using genealogy data as an example. Finally, the challenges and opportunities of fragmented data fusion are also discussed. |
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| Keywords: | fragmented data data fusion genealogy data multiple heterogeneous sources HAO intelligence model |
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