The Ranking of Deep Web Sources Based on Data Quality

被引:0
|
作者
Yin, Hu [1 ]
Lv, Yunfei [2 ]
Wang, Weiwei [2 ]
机构
[1] 719 Inst Technol Wuhan, Wuhan, Peoples R China
[2] Wuhan Second Ship Design Inst, Wuhan, Peoples R China
关键词
Sampling estimates; Data quality; Quality Vector; Deep Web ranking;
D O I
10.4028/www.scientific.net/AMM.303-306.2437
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Deep Web technology makes a large number of useful information which hidden behind the interface easier to be found by users. However, with the increase of data source, how to find a suitable result quickly from a number of sources is becoming more and more important. In this paper, we start discussing from the quality of the data, setting 6 quality standards for the data source and giving the method of calculation. Meanwhile, we solve corresponding weight vector of quality standards by the feeling of the users; and based on this quality standards, we calculate a random data source according to weight vector to gain a general score. Then this paper discusses the sampling theory and proposes a reasonable sampling method for the experiment. The experiment result shows that it is of good veracity and operability to evaluate and score the data quality of data source according to sampling analysis.
引用
收藏
页码:2437 / +
页数:2
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