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This paper has brought about a novel method based on multi-view algorithms for learning from positive and unlabeled examples (LPU). First we, with an improved 1-DNF method, split the text feature into a positive feature set (PF) and a negative feature set (NF). And we project each text vector on the two feature sets in turn. Then we use the co-EM SVM algorithm, which was previously used for semi-supervised...
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