| Authors: | Kourtis I., Stamatatos E. |
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| Title: | Author Identification Using Semi-supervised Learning |
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| Conference: | 5th Int. Workshop on Uncovering Plagiarism, Authorship, and Social Software Misuse (PAN-11) |
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| Year: | 2011 |
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| Abstract: | Author identification models fall into two major categories according to the way they handle the training texts: profile-based models produce one representation per author while instance-based models produce one representation per text. In this paper, we propose an approach that combines two well-known representatives of these categories, namely the Common n-Grams method and a Support Vector Machine classifier based on character n-grams. The outputs of these classifiers are combined to enrich the training set with additional documents in a repetitive semi-supervised procedure inspired by the co-training algorithm. The evaluation results on closed-set author identification are encouraging, especially when the set of candidate authors is large. |
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Greek