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As almost all the successful author identification approaches are based on the word frequencies, the most obvious way to obfuscate a text is to distort those frequencies. In this paper we chose a subset of the most frequent words for an author and replace each one with one of their synonyms. In order to select the best synonym, we considered two measures:(More)
The Author Identification task for PAN 2016 consisted of three different Sub-tasks: authorship clustering, authorship links and author diarization. We developed a machine learning approaches for two of three of these tasks. For the two authorship related tasks we created various sets of feature spaces. The challenge was to combine these feature spaces to(More)
This report explains our Persian plagiarism detection system which we used to submit our run to Persian PlagDet competition at FIRE 2016. The system was constructed through four main stages. First is pre-processing and tokenization. Second is constructing a corpus of sentences from combination of source and suspicious document pair. Each sentence considered(More)
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