Today, there are many documents on Internet, such that users can generate new documents by coping them and existing Plagiarism Detection systems (PDS) couldn't detect all kind of plagiarism. The main challenge is finding a suitable algorithm to improving the amount of similar documents and their assessing time. It’s difficult to do assessing similarity in Persian texts that different characteristics affect on it and also many of them are ambiguous. For this reason Dempster - Shefer (Evidence) theory has been used in this paper. The proposed system will assess in a two-level and in the first stage, sentences will divide in general and expert terms and then assessing by suitable measures and domain ontology. These results will be delivered to first level as "basic belief" and will be integrated by using a Dempster combination rule to create one of the second level inputs. In second level, the previous level result and another similarity measures will be weighted and combined belief and plausibility functions for final assessment will be distinguished. This system has been used for real data assessment and compared the actual results shows that the precision between the system results and actual results is about 90%, which implies that the system can be used as Plagiarism Detection System.
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