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《山东大学学报(理学版)》 ›› 2020, Vol. 55 ›› Issue (1): 41-50.doi: 10.6040/j.issn.1671-9352.1.2019.105

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基于多粒度的多源数据知识获取

万青1,2*,马盈仓1,魏玲2,3   

  1. 1.西安工程大学理学院, 陕西 西安 710048;2. 西北大学概念认知与智能研究中心, 陕西 西安 710127;3.西北大学数学学院, 陕西 西安 710127
  • 发布日期:2020-01-10
  • 作者简介:万青(1986— ),女,博士,讲师,研究方向为粗糙集、概念格和粒计算. E-mail:wqysbe@163.com*通信作者
  • 基金资助:
    国家自然科学基金资助项目(61772021,61976130);陕西省教育厅专项基金(19JK0380)

Knowledge acquisition of multi-source data based on multigranularity

WAN Qing1,2*, MA Ying-cang1, WEI Ling2,3   

  1. 1. School of Science, Xian Polytechnic University, Xian 710048, Shaanxi, China;
    2. Institute of Concepts, Cognition and Intelligence, Northwest University, Xian 710127, Shaanxi, China;
    3. School of Mathematics, Northwest University, Xian 710127, Shaanxi, China
  • Published:2020-01-10

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摘要： 多粒度认知能力是人类分析复杂数据的一种常用策略。作为复杂数据类型之一的多源数据,因其数据源头多而使得数据分析变得复杂。受多粒度思想的启发,以多源信息系统为数据基础,基于悲观的决策策略,提出了多源划分约简集的定义。讨论了多源划分约简集与划分约简集之间的关系,并给出了相应的属性特征的判别方法。最后,针对多源决策信息系统,基于乐观的决策策略,提出了多源决策规则。借鉴多粒度模型,从一个新角度所提出的多源数据分析方式进一步丰富了知识获取的方法。

关键词: 多粒度, 多源信息系统, 属性约简, 多源决策规则

Abstract: Multigranularity cognition is the common strategy for analyzing complex data. Multi-source data is one type of the complex data, and its knowledge acquisition become more complicated because of its multisource. Inspired by the idea of multigranularity, the multi-source attribute reduction is defined based on the pessimistic decision-making strategy in multi-source information systems. The relationships between the multi-source attribute reduction and the attribute reduction are discussed in detail, and the corresponding judgment method of attribute characteristics are given. Finally, the definition of multi-source decision rule is proposed based on the optimistic decision-making strategy in multi-source decision information systems. On the basis of multi-granularity model, the proposed method gives a new perspective of multi-source data analysis, which enriches the study of knowledge acquisition.

Key words: multigranularity, multi-source information system, multi-source attribute reduction, multi-source decision rule

中图分类号: 

  • TP18
[1] YAGER R R. A framework for multi-source data fusion[J]. Information Sciences, 2004, 163(1/2/3): 175-200.
[2] KHAN M A, BANERJEE M. Formal reasoning with rough sets in multiple-source approximation systems[J]. International Journal of Approximate Reasoning, 2008, 49(2):466-477.
[3] LIN Guoping, LIANG Jiye, QIAN Yuhua. An information fusion approach by combining multigranulation rough sets and evidence theory[J]. Information Sciences, 2015, 314:184-199.
[4] XU Weihua, YU Jianhang. A novel approach to information fusion in multi-source datasets: a granular computing viewpoint[J]. Information Sciences, 2017, 378:410-423.
[5] CHE Xiaoya, MI Jusheng, CHEN Degang. Information fusion and numerical characterization of a multi-source information system[J]. Knowledge-Based Systems, 2018, 145:121-133.
[6] WEI Wei, LIANG Jiye. Information fusion in rough set theory: an overview[J]. Information Fusion, 2019, 48:107-118.
[7] WU Weizhi, LEUNG Yee. Theory and applications of granular labelled partitions in multi-scale decision tables [J]. Information Sciences, 2011, 181(18):3878-3897.
[8] GANTER B, WILLE R. Formal concept analysis: mathematical fundations[M]. New York: Springer-Verlag, 1999.
[9] 曾望林, 折延宏. 面向对象的多粒度形式概念分析[J]. 计算机科学, 2018,45(10):58-60. ZENG Wanglin, SHE Yanhong. Object-oriented multigranulation formal concept analysis[J]. Computer Science, 2018, 45(10):58-60.
[10] 李金海, 吴伟志, 邓硕. 形式概念分析的多粒度标记理论[J]. 山东大学学报(理学版), 2019, 54(2):30-40. LI Jinhai, WU Weizhi, DENG Shuo. Multi-scale theory in formal concept analysis[J]. Journal of Shandong University(Natural Science), 2019, 54(2): 30-40.
[11] 吴伟志, 陈颖, 徐优红, 等. 协调的不完备多粒度标记决策系统的最优粒度选择[J]. 模式识别与人工智能, 2016, 29(2):108-115. WU Weizhi, CHEN Ying, XU Youhong, et al. Optimal granularity selections in consistent incomplete multi-granular labeled decision systems[J]. Pattern Recognition and Artificial Intelligence, 2016, 29(2):108-115.
[12] WU Weizhi, QIAN Yuhua, LI Tongjun, et al. On rule acquisition in incomplete multi-scale decision tables[J]. Information Sciences, 2017, 378:282-302.
[13] SHE Yanhong, LI Jinhai, YANG Hailong. A local approach to rule acquisition in multi-scale decision tables[J]. Knowledge-Based Systems, 2015, 89:398-410.
[14] HAO Chen, LI Jinhai, FAN Min, et al. Optimal scale selection in dynamic multi-scale decision tables based on sequential three-way decisions[J]. Information Sciences, 2017, 415:213-232.
[15] LI Feng, HU Baoqing. A new approach of optimal scale selection to multi-scale decision tables[J]. Information Sciences, 2017, 381:193-208.
[16] LI Feng, HU Baoqing, WANG Jun. Stepwise optimal scale selection for multi-scale decision tables via attribute significance[J]. Knowledge-Based Systems, 2017, 129:4-16.
[17] 顾沈明, 陆瑾璐, 吴伟志, 等. 广义多尺度决策系统的局部最优粒度选择[J]. 山东大学学报(理学版), 2018, 53(8):4-11. GU Shenming, LU Jinlu, WU Weizhi, et al. Local optimal granularity selections in generalized multi-scale decision systems[J]. Journal of Shandong University(Natural Science), 2018, 53(8):4-11.
[18] XIE Junpin, YANG Minhua, LI Jinhai, et al. Rule acquisition and optimal scale selection in multi-scale formal decision contexts and their applications to smart city[J]. Future Generation Computer Systems, 2018, 83:564-581.
[19] QIAN Yuhua, LIANG Jiye. Rough set method based on multi-granulations[C] // Proceeding of 5th IEEE Conference on Cognitive Informatics. Beijing: IEEE Computer Society, 2006: 297-304.
[20] QIAN Yuhua, LIANG Jiye, YAO Yiyu, et al. MGRS: a multi-granulation rough set[J]. Information Sciences, 2010, 180(6):949-970.
[21] 王丽娟, 杨习贝, 杨静宇, 等. 一种新的不完备多粒度粗糙集[J]. 南京大学学报(自然科学), 2012, 48(4):436-444. WANG Lijuan, YANG Xibei, YANG Jingyu, et al. A new incomplete multigranulation rough sets[J]. Journal of Nanjing University(Natural Science), 2012, 48(4):436-444.
[22] LIU Caihui, MIAO Duoqian, QIAN Jin. On multi-granulation covering rough sets[J]. International Journal of Approximate Reasoning, 2014, 55(6):1404-1418.
[23] HUANG Bing, GUO Chunxiang, ZHUANG Yuliang, et al. Intuitionistic fuzzy multigranulation rough sets[J]. Information Sciences, 2014, 277:299-320.
[24] ZHANG Xiaohong, MIAO Duoqian, LIU Caihui, et al. Constructive methods of rough approximation operators and multigranulation rough sets[J]. Knowledge-Based Systems, 2016, 91:114-125.
[25] 张文修, 仇国芳. 基于粗糙集的不确决策[M]. 北京, 清华大学出版社, 2005. ZHANG Wenxiu, QIU Guofang. Uncertain decision making based on rough sets[M]. Beijing: Tsinghua University Press, 2005.
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