Semi-supervised approach to rapid and reliable labeling of large data sets


In this paper, we propose a method, where the labeling of the data set is carried out in a semi-supervised manner with user-specified guarantees about the quality of the labeling. In our scheme, we assume that for each class, we have some heuristics available, each of which can identify instances of one particular class. The heuristics are assumed to have… (More)
DOI: 10.1145/1401890.1401968


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