Computer Science and Applications

Duplicate Field Matching for Data Cleaning of Chinese Placenames

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  • 1. School of Computer Science and Engineering, Xi’an University of Technology, Xi’an 710048, China
    2. State Key Laboratory for Manufacturing Systems Engineer, Xi’an Jiaotong University, Xi’an 710048, China

Received date: 2012-03-15

  Revised date: 2012-07-18

  Online published: 2012-07-18

Abstract

To improve accuracy of field matching of Chinese placenames, an approximate duplicate detection and cleaning strategy and a matrix approximate duplicate matching method are proposed. In the strategy, a matrix approximate duplicate matching method is used. Frequencies of the same Chinese characters or word between two Chinese placenames can first be calculated with a matrix operation. Semantic similarity and structure similarity can be calculated using the frequencies. By combining semantic and structure similarities, they are considered as the basis of duplicate detection and data cleaning. Simulation experiments are conducted to prove feasibility and validity of the method, showing that the matrix approximate duplicate matching method is better than other existing methods in terms of precision and recall ratio.

Cite this article

YE Ou1, ZHANG Jing1,2, LI Jun-huai1 . Duplicate Field Matching for Data Cleaning of Chinese Placenames[J]. Journal of Applied Sciences, 2013 , 31(2) : 212 -220 . DOI: 10.3969/j.issn.0255-8297.2013.02.017

References

[1]郭志懋,周傲英.数据质量和数据清洗研究综述 [J].软件学报,2002, 13(11): 2076-2082.
[2]FAN Wenfei. Extending dependencies with conditions for data cleaning [J].2008 8th IEEE International Conference on: Computer and Information Technology, 2008: 185-190.
[3]NEELY M P. Data quality tools for data warehousing: a small sample survey [C]// Proceedings of MIT Conference on Information Quality, Center for Technology in Government, University at Albany/ SUNY: Germany (1998).
[4]QIU Yuefeng, TIAN Zongping, JI Wenyun. An efficient approach for detecting approximately duplicate database records [J].Chinese Journal of Computers, 2001, 24(1): 69-77.
[5]EKTEFA M, SIDI F, IBRAHIM H, JABAR M A, MEMAR S, RAMLI A.A threshold-based similarity measure for duplicate detection [C]//2011 IEEE Conference on Open Systems(ICOS), 2011: 37-41.
[6]TREVOR C K.Automated detection of duplicate free-form English bug reports [J].MS Computer Science Thesis, Department of Computer Science, Morgantown, West Virginia, USA, 2009, West Virginia University.
[7]RUNESON P, ALEXANDERSSON M, NYHOLM O.Detection of duplicate defect reports using natural language processing [C]//ICSE 2007: Proceedings of the 29th international conference on Software Engineering,  Washington, DC, USA, 2007: 499-510.
[8]NARAYANA V A, PREMCHAND P, GOVARDHAN A.A novel and efficient approach for near duplicate page detection in Web crawling [C]//2009 IEEE International Advance Computing Conference (IACC), 2009: 1492-1496.
[9]WANG Bin, LI Zhiwei, LI Mingjing, MA Weiying.Large-scale duplicate detection for Web image search [C]//2006 IEEE International Conference on Multimedia and Expo, 2006: 353-356.
[10]MASEK W, PATERSON M A.Fast algorithm computing string edit distance [J].Journal of Computer System Science, 1980, 20(1): 18-31.
[11]LIAO Hsienyu, MENG_Laiyin, YI Cheng.A parallel implementation of the Smith-Waterman algorithm for massive sequences searching [C]//IEMBS’04.26th Annual International Coference of the IEEE: Engineering in Medicine and Biology Society, 2004, 2: 2817-2820.
[12]WINKLER W E. The state record linkage and current research problems [J].Technical report, Statistics of Income Division, Internal Revenue Service Publication (1999).
[13]LI Guohui, DU Xiaokun, HU Fangxiao, YANG Bing, TANG Xiaohong.Structure matching method based on functional dependencies [J].Journal of Software, 2009, 20(10): 2667-2678.
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