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	Large-scale similarity join with edit-distance constraints
	Lin, Che ; Yu, Haiyang ; Weng, Wei ; He, Xianmang ; Lin C(林琛)
	2014
关键词	Algorithms
英文摘要	Conference Name:19th International Conference on Database Systems for Advanced Applications, DASFAA 2014. Conference Address: Bali, Indonesia. Time:April 21, 2014 - April 24, 2014.; In the age of big data, the data quality problem is more severe than ever. As an essential step in data cleaning, similarity join has attracted lots of attentions from the database community. In this work, to address the similarity join problem with edit-distance constraints, we first improve the partition-based join algorithm for small scale data. Then we extend the algorithm based on MapReduce framework for large-scale data. Extensive experiments on both real and simulated datasets demonstrate the efficiency of our algorithms. ? 2014 Springer International Publishing Switzerland.
语种	英语
出处	http://dx.doi.org/10.1007/978-3-319-05813-9-22
出版者	Springer Verlag
内容类型	其他
源URL	[http://dspace.xmu.edu.cn/handle/2288/86950]
专题	信息技术－会议论文
推荐引用方式 GB/T 7714	Lin, Che,Yu, Haiyang,Weng, Wei,et al. Large-scale similarity join with edit-distance constraints. 2014-01-01.

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