Abstract
With the development of the Internet, lots of data appears on the Internet. But these data can’t be efficiently used owing to the lack of validity and believability, so data trust assessment has become a hot topic in the current research in the field of web. Considering the close relationship between the data credibility and its provenance, this paper proposes its own quantization rules with the existing trust evaluation model. And because of the similarities between web pages and RDF data, the improved PageRank algorithm is put forwarded in order to filter invalid data set. At last, the DataHub dataset is used to carry out a comprehensive experiment. The experimental results which carried out with DataHub set show that the proposed quantization rule and the improved PageRank algorithm can greatly improve the sorting result of the data set and reduce the effect of invalid data set on the sorting result.
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Wei, K., Tian, P., Gu, J., Huang, L. (2017). RDF Data Assessment Based on Metrics and Improved PageRank Algorithm. In: Bao, Z., Trajcevski, G., Chang, L., Hua, W. (eds) Database Systems for Advanced Applications. DASFAA 2017. Lecture Notes in Computer Science(), vol 10179. Springer, Cham. https://doi.org/10.1007/978-3-319-55705-2_16
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DOI: https://doi.org/10.1007/978-3-319-55705-2_16
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