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When in addition to node contents and labels, relations (links) between nodes and some unlabeled nodes are available, collective classification algorithms can be used. Collective classification algorithms, like ICA (Iterative Classification Algorithm), determine labels for the unlabeled nodes based on the contents and/or labels of the neighboring nodes.(More)
Finding new peptides that can bind to some inorganic materials with high affinity and specificity is an active research problem with many application areas ranging from medicine to electronics. While it is easier to design peptides in-silico, in-vitro testing of binding is a slow and expensive process. Peptides with similar structure usually have similar(More)
Collective classification algorithms [Mackassky et.al. 2007, Sen et.al. 2008] could be used for better classification of networked data when unlabeled test node features and links are available. In this study, we provide detailed results on the performance of collective classification algorithms when content or link noise is present. First of all, we show(More)
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