Hamtajoo: A Persian Plagiarism Checker for Academic Manuscripts

TL;DR

Hamtajoo is a novel Persian plagiarism detection system designed for academic manuscripts, addressing challenges in semantic text re-use detection and low-resource language NLP applications.

Contribution

The paper introduces Hamtajoo, a comprehensive Persian plagiarism detection system with detailed algorithms, tailored for low-resource language contexts and evaluated on PAN standards.

Findings

Effective detection of semantically altered plagiarism patterns.

High performance on PAN plagiarism detection corpus.

Addresses challenges in low-resource language NLP.

Abstract

In recent years, due to the high availability of electronic documents through the Web, the plagiarism has become a serious challenge, especially among scholars. Various plagiarism detection systems have been developed to prevent text re-use and to confront plagiarism. Although it is almost easy to detect duplicate text in academic manuscripts, finding patterns of text re-use that has been semantically changed is of great importance. Another important issue is to deal with less resourced languages, which there are low volume of text for training purposes and also low performance in tools for NLP applications. In this paper, we introduce Hamtajoo, a Persian plagiarism detection system for academic manuscripts. Moreover, we describe the overall structure of the system along with the algorithms used in each stage. In order to evaluate the performance of the proposed system, we used a plagiarism detection corpus comply with the PAN standards.