The Ranking of Deep Web Sources Based on Data Quality

Abstract:

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.

• Periodical: Applied Mechanics and Materials (Volumes 303-306)
• Pages: 2437-2444
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.303-306.2437
• Online since: February 2013
• Authors: Hu Yin, Yun Fei Lv, Wei Wei Wang
• Keywords: Data Quality, Deep Web Ranking, Quality Vector, Sampling Estimates

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