The Ranking of Deep Web Sources Based on Data Quality

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 discuss...

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Bibliographic Details
Published inApplied Mechanics and Materials Vol. 303-306; pp. 2437 - 2444
Main Authors Wang, Wei Wei, Yin, Hu, Lv, Yun Fei
Format Journal Article
LanguageEnglish
Published Zurich Trans Tech Publications Ltd 01.02.2013
Subjects
Deep Web Ranking
Data Quality
Quality Vector
Sampling Estimates
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Summary: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.
Bibliography:Selected papers from the 2012 International Conference on Sensors, Measurement and Intelligent Materials (ICSMIM 2012), December 26-27, 2012, Guilin, China
ISBN:3037856521
9783037856529
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.303-306.2437