The problem of plagiarism the recent years has been intensified by the availability of information in digital form and the accessibility of the electronic libraries through the Internet. As a result, plagiarism detection has been transformed into a big data analytics problem since the number of digital sources is extravagant and a new document needs to be compared with millions of other existing documents. In this paper, a text mining methodology is proposed that can detect all common patterns between a document and the documents in a reference database. The technique is based on a pattern detection algorithm and the corresponding data structure that enables the algorithm to detect all common patterns. The methodology has been applied in a well-defined dataset providing very promising results identifying difficult cases of plagiarism such as technical disguise.
展开▼
