Persian Plagiarism Detection Using Sentence Correlations

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 to be a document and represented as a tf-idf vector. Third step is to construct a similarity matrix between source and suspicious document. Finally the most similar documents which their similarity is higher than a specific threshold marked as plagiarized segments. Our performance measures on the training corpus were promising (precision=0.914, recall=0.848, granularity=3.85). CCS Concepts • Information systems➝Information retrieval ➝Retrieval tasks and goals. Near-duplicate and plagiarism detection. [1] [2] [3] [4] [5] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17]