Plagiarism is an illicit act of using other‟s work wholly or partially as one‟s own in any field such as art, poetry literature, cinema, research and other creative forms of study. It has become a serious crime in academia and research fields and access to wide range of resources on the internet has made the situation even worse. Therefore, there is a need for automatic detection of plagiarism ...

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...

Currently there is an increase in the occurrence of plagiarism in varied types of academic texts. Therefore, in agreement with the Brazilian Coordination of Improvement of Higher Education Personnel (CAPES) policies, Brazilian higher education institutions should establish guidelines for the detection and inhibition of academic plagiarism. However, the notion of plagiarism is extremely complex,...

This paper reports on a pilot project of the Turnitin plagiarism detection software, which was implemented to determine the impact of the software on the level of plagiarism among University of Botswana (UB) students. Students’ assignments were first submitted to the software without their knowledge so as to gauge their level of plagiarism. The results recorded the average level of plagiarism a...

In this paper we report on our plagiarism detection system which is used to process the PAN plagiarism corpus for the tasks of Candidate Document Retrieval and Detailed Comparison. To retrieve the plagiarism candidate document by using ChatNoir API, a method based on tf*idf to extract the keywords of suspicious documents as queries is proposed. An Lucene ranking method is used for plagiarism ca...

The plagiarism detection system described in this paper is aiming at bringing external plagiarism detection to the desktop. The main ideas are to incorporate standard IR technologies for the candidate selection and efficient data structures for the detailed analysis between a suspicious and a candidate document. Given that the system so far has only reached prototype status, the first results l...

The paper discusses about the problem of Authorship analysis, different types of authorship analysis’s such as authorship attribution, authorship identification, authorship profiling, plagiarism detection. It also addresses the issues in Indian language text. Keywords— Authorship attribution, authorship profiling, plagiarism detection, text classification.

Paraphrase plagiarism is one of the difficult challenges facing plagiarism detection systems. Paraphrasing occur when texts are lexically or syntactically altered to look different, but retain their original meaning. Most plagiarism detection systems (many of which are commercial based) are designed to detect word co-occurrences and light modifications, but are unable to detect severe semantic ...

Current research in the field of automatic plagiarism detection for text documents focuses on algorithms that compare plagiarized documents against potential original documents. Though these approaches perform well in identifying copied or even modified passages, they assume a closed world: a reference collection must be given against which a plagiarized document can be compared. This raises th...

There exist many plagiarism detection tools to uncover plagiarized codes by analyzing the similarity of source codes. To measure how reliable those plagiarism detection tools are, we developed a tool named Code ObfuscAtion Tool (COAT) that takes a program source code as input and produces another source code that is exactly equivalent to the input source code in their functional behaviors but w...