Background & Purpose: The increasing of communication networks has made easy to access scientific literature of researchers. In the meantime, the profiteers are trying to copy the works and ideas of others to achieve their destinations, in the shortest time and without effort. In recent decades, this problem called plagiarism has spread to various scientific communities. The purpose of this study is to design an intelligent model for detecting plagiarism in Persian Language.
Methodology: The type of research is applied and method of research in the first step is to identify the dimensions of the model, exploratory, in second stage, comparative study of selected models and in the third stage, analytical, and in the fourth stage, due to the software testing of the model is experimental. The data collection tool is interviews with 10 experts. In the following, comparative study of selected models was performed and after analyzing the interview with experts, the final model was designed.
Findings: After testing model using the Robinson model, phrases and phrases that were similar to the original text were identified by the software and the terms were represented in four clusters and with four different colors.
Conclusion: The result is that the use of structural and semantic analysis methods, sequentially, can lead to the diagnosis of plagiarism and the prevention of repetitive content in Persian language.