[1]胡文彬,潘祝山,纪兆辉.模式匹配不确定性的多因素集结度量[J].智能系统学报,2015,10(2):286-292.[doi:10.3969/j.issn.1673-4785.201405061]
HU Wenbin,PAN Zhushan,JI Zhaohui.Uncertain measure for schema matching based on the aggregation of uncertain factors[J].CAAI Transactions on Intelligent Systems,2015,10(2):286-292.[doi:10.3969/j.issn.1673-4785.201405061]
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HU Wenbin,PAN Zhushan,JI Zhaohui.Uncertain measure for schema matching based on the aggregation of uncertain factors[J].CAAI Transactions on Intelligent Systems,2015,10(2):286-292.[doi:10.3969/j.issn.1673-4785.201405061]
模式匹配不确定性的多因素集结度量
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
10
期数:
2015年第2期
页码:
286-292
栏目:
学术论文—机器感知与模式识别
出版日期:
2015-04-25
- Title:
- Uncertain measure for schema matching based on the aggregation of uncertain factors
- Keywords:
- schema definition; schema analysis; schema matching; uncertainty analysis; measured data uncertainty; measurement method; decision analysis; entropy; aggregation estimation method
- 分类号:
- TP18;TP391
- 文献标志码:
- A
- 摘要:
- 为了能够有效度量模式匹配的不确定性,提出了一个模式匹配不确定性的度量模型,根据不确定性因素间的关系提出了一个集结算子。使用全知熵度量语义匹配和属性匹配的不确定性,引入过程不确定性的度量方法度量匹配决策过程的不确定性。使用多因素集结算子判断各因素的影响程度,并可合成各度量结果。实验证明,所提模型和方法能够有效度量模式匹配的不确定性,且具有高效性和可扩展性。
- Abstract:
- To measure efficiently uncertainty of schema matching, a measure model based on all uncertain factors was proposed and an aggregation operator was given according to the relations of uncertain factors. A measure method of semantic matching and attribute matching based on all known entropy uncertain ratio was designed. A measure algorithm of process uncertainty was introduced to measure uncertainty of a decision making process. The aggregation operator based on relationships between uncertain factors was proposed to determine influence degree of uncertain factors and merge all measure values in the measure process. The real world examples illustrate that the proposed model and methods can completely reflect three factors of uncertainty and can measure efficiently uncertainty for schema matching. The proposed methods are efficient and scalable.
- 参考文献/References:
-
[1] SHVAIKO P, EUZENAT J. A survey of schema-based matching approaches[J]. Journal on Data Semantics IV, 2005(3730): 146-171.
[2] MAGNANI M, RIZOPOULOS N, BRIEN P, et al. Schema integration based on uncertain semantic mappings[J]. Lecture Notes in Computer Science, 2005(3716): 31-46.
[3] HALEVY A, RAJARAMAN A, ORDILLE J. Data integration:the teenage years[Z]. Seoul, 2006: 9-16.
[4] 翁年凤,刁兴春,曹建军,等. 不确定模式匹配研究综述[J]. 计算机科学, 2011, 38(12): 1-5.WENG Nianfeng, DIAO Xingchun, CHAO Jianjun, et al. Survey of uncertain schema matching[J]. Computer Science, 2011, 38(12): 1-5.
[5] 姜芳艽,孟小峰,贾琳琳. Deep Web 集成服务的不确定模式匹配[J]. 计算机学报, 2008, 31(8): 1412-1421.JIANG Fangjiao, MENG Xiaofeng, JIA Linlin. Uncertain schema matching in deep web integration service[J]. Chinese Journal of Computers, 2008, 31(8): 1412-1421.
[6] MAGNANI M, MONTESI D. Probabilistic data integration[R]. Bologna(italy): UBLCS, 2009.
[7] DONG X L, HALEVY A, YU CONG. Data integration with uncertainty[J]. The VLDB Journal, 2009, 18: 469-500.
[8] AVIGDOR G. Managing uncertainty in schema matching with top-k schema mappings[J]. Journal on Data Semantics, 2006, 6: 90-114.
[9] LIU Baoding. Uncertainty theory[M]. Berlin: Springer-Verlag, 2007: 3-12.
[10] LIU Baoding. Some research problems in uncertainty theory[J]. Journal of Uncertain Systems, 2009, 3(1): 3-10.
[11] 王永利,钱江波,孙淑荣. AMUR:一种RFID数据不确定性的自适应度量算法[J]. 电子学报, 2011, 39(3): 579-584.WANG Yongli, QIAN Jiangbo, SUN Shurong. AMUR: an adaptive measuring algorithm of underlying uncertainty for rfid data[J]. Chinese of Journal Electronics, 2011, 39(3): 579-584.
[12] PAWLAL Z. Rough sets[J]. International Journal of Computer and Information Science, 1982, 11(5): 341-356.
[13] QIU Taorong, YOU Min, GE Hanjuan, et al. A method of uncertainty measure based on rough set[Z]. 2008: 544-547.
[14] JIANG Feng, SUI Yuefei, CAO Cungen. An information entropy-based approach to outlier detection in rough sets[J]. Expert Systems with Applications, 2010, 37(9): 6338-6344.
[15] LIANG Jiye, WANG Junhong, QIAN Yuhua. A new measure of uncertainty based on knowledge granulation for rough sets[J]. Information Sciences, 2009, 179(4): 458-470.
[16] IFTIKHAR-U S, ARYYA G. Managing uncertainty in location services using rough set and evidence theory[J]. Expert System with Application, 2007, 32(2): 386-396.
[17] 胡文彬,李千目,张宏. 基于领域知识的不确定性关系模式集成[J]. 南京理工大学学报:自然科学版, 2010, 34(4): 409-414.HU Wenbin, LI Qianmu, ZHANG Hong. Uncertain relation schema integration based on domain knowledge[J]. Journal of Nanjing University of Science and Technology: Natural Science, 2010, 34(4): 409-414.
[18] 胡文彬,张宏,李千目. 基于全知熵的模式集成不确定性度量模型[J]. 南京航空航天大学学报, 2012, 44(4): 575-579.HU Wenbin, ZHANG Hong, LI Qianmu. Uncertainty measure model of schema integration based on all known entropy[J]. Journal of Nanjing University of Aeronautics & Astronautics, 2012, 44(4): 575-579.
[19] WANG J G, MENG G Y, ZHENG X L. The attribute reduce based on rough sets and sat algorithm[Z]. 2008: 98-102.
[20] LIANG Jiye, QIAN Yuhua. Information granules and entropy theory in information systems[J]. Science in China Series F: Information Sciences, 2008, 51(10): 1427-1444.
[21] 赵军,周应华. 基于粗集理论的系统不确定性度量方式研究[J]. 小型微型计算机系统, 2010, 31(2): 354-359.ZHAO Jun, ZHOU Yinghua. Study on system uncertainty measures based on rough set theory[J]. Journalof Chinese Computer Systems, 2010, 31(2): 354-359.
[22] YU Daren, HU Qinghua, WU Congxin. Uncertainty measures for fuzzy relations and their applications[J]. Applied Soft Computing, 2007, 7(3): 1135-1143.
[23] 胡军,王国胤. 粗糙集的不确定性度量准则[J]. 模式识别与人工智能, 2010, 23(5): 606-615.HU Jun, WANG Guoyin. Uncertainty measure rule sets of rough sets[J]. Pattern Recognition and Artificial Intelligence. 2010, 23(5): 606-615.
[24] MAGNANI M, MONTESI D. Uncertainty in data integration:current approaches and open problems[M]. Enschede, The Netherlands: the Centre for Telematics and Information Technology, 2007: 26-32.
[25] JUNG J Y, CHIN C H, CARDOSO J. An entropy-based uncertainty measure of process models[J]. Information Processing Letters, 2011, 111(3): 135-141.
[26] 岳昆,刘惟一,王晓玲. 一种基于不确定性因素叠加的Web服务质量度量方法[J]. 计算机研究与发展, 2009, 46(5): 841-849.YUE Kun, LIU Weiyi, WANG Xiaoling. An approach for measuring quality of web services based on the superposition of uncertain factors[J].Journal of Computer Research and Development, 2009, 46(5): 841-849.
备注/Memo
收稿日期:2014-6-6;改回日期:。
基金项目:国家自然科学基金资助项目(60903027);江苏省自然科学重大研究项目资助项目(BK2011023);江苏省自然科学基金资助项目(BK2011370).
作者简介:胡文彬,女,1976年生,博士,中国计算机学会会员,主要研究方向为数据集成、社会网络、隐私保护,作为主要成员完成省级课题1项,参与完成市级课题2项。发表学术论文10余篇,其中被EI检索3篇;潘祝山,男,1968年生,副教授,主要研究方向为人工智能、确定性理论。参与省市级课题多项;纪兆辉,男,1971年生,副教授,中国计算机学会高级会员,主要研究方向为数据挖掘、语义Web、多Agent等。发表学术论文20余篇,主持、参与省市级科研课题10余项。
通讯作者:胡文彬.E-mail:hwb1008@163.com.
更新日期/Last Update:
2015-06-15