Plagiarism detection service to be launched in June

Plagiarism Detection

detection procedure consisted of automatic scanning of manuscripts using plagiarism detection software (eTBLAST and CrossCheck) and manual verification of manuscripts suspected of having been plagiarized (more than 10% text similarity). They found that 11% of manuscripts were plagiarized, 8% were true plagiarism, and 3% were self-plagiarism. The Korean Journal of family medicine (KJFM) has also...

Plagiarism Detection in Computer Code

The ease with which computer code can be copied by students presents opportunities for plagiarism on programming projects. Presently, instructors are provided with few tools (if any) that assist them in detecting possible plagiarism in an assignment. Therefore, the only solution is a tedious and error prone by hand check of student submissions, looking for similarity between any two. In this th...

Plagiarism Detection in Source Code

Plagiarism Detection in Java Code

iii Acknowledgement We feel a great sense of accomplishment to be able to complete this thesis, as part of the requirement for our Master " s degree. We would have not been able to do this on our own without the supports of the people whom are important to us. Firstly, we would like to thank our supervisor, Associate Professor Dr. Jonas Lundberg for his continuous support and guidance. His advi...

A Set-Based Approach to Plagiarism Detection

This paper describes our approach to the Detailed Analysis subtask of the PAN 2012 competition. Our experiments deal with monolingual plagiarism cases, only. We use a simple set-based algorithm, that employs Dice’s coefficient as a similarity measure. Furthermore we employ basic strategies from Information Retrieval and Natural Language Processing for stop word removal and language detection. W...