Improving Classification Quality in Uncertain Graphs

Journal of Data and Information Quality, pp. 1-20, 2019.

Cited by: 0|Bibtex|Views62|DOI:https://doi.org/10.1145/3242095
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Other Links: dblp.uni-trier.de|academic.microsoft.com|dl.acm.org

Abstract:

In many real applications that use and analyze networked data, the links in the network graph may be erroneous or derived from probabilistic techniques. In such cases, the node classification problem can be challenging, since the unreliability of the links may affect the final results of the classification process. If the information abou...More

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