Plagiarism detection

About: Plagiarism detection is a research topic. Over the lifetime, 1790 publications have been published within this topic receiving 24740 citations.

Combination of Cosine Similarity Method and Conditional Probability for Plagiarism Detection in the Thesis Documents Vector Space Model

Abstract: Plagiarism is one of negative impact derived from the internet growth. It can take place in various place, one of the examples is higher education environment. Plagiarism can cause many disadvantageous to other parties. So, there must be a detection system to avoid this kind of bad thing. In this proposed research, there will be made a plagiarism detection system by implementing Vector Space Model (VSM). Cosine Similarity used to make the rank of the paragraphs based on the formed angle from query vector and collection vector. The number of the taken words from the query paragraph will be derived from the calculation of the conditional probability value. After testing phase has been finished, there will be a conclusion that VSM can be implemented in the system. There are 10 testing paragraphs that compared with the collection paragraphs. The best result shows from threshold 0.3 for the conditional probability and 0.2 for cosine similarity with 54.28% for the average precision and 100% for the average recall.

CodEX: Source Code Plagiarism Detection Based on Abstract Syntax Tree.

Abstract: CodEX is a source code search engine that allows users to search a repository of source code snippets using source code snippets as the query also. A potential use for such a search engine is to help educators identify cases of plagiarism in students’ programming assignments. This paper evaluates CodEX in this context. Abstract Syntax Trees (ASTs) are used to represent source code files on an abstract level. This, combined with node hashing and similarity calculations, allows users to search for source code snippets that match suspected plagiarism cases. A number of commonly-employed techniques to avoid plagiarism detection are identified, and the CodEX system is evaluated for its ability to detect plagiarism cases even when these techniques are employed. Evaluation results are promising, with 95% of test cases being identified

Document copy detection system based on plagiarism patterns

Abstract: Document copy detection is a very important tool for protecting author’s copyright. We present a document copy detection system that calculates the similarity between documents based on plagiarism patterns. Experiments were performed using CISI document collection and show that the proposed system produces more precise results than existing systems.

Teaching Acknowledgement Practice Using the Internet-Based Plagiarism Detection Service

Abstract: Instead of focusing on detecting and punishing plagiarism, this teaching innovation uses the Internet-based plagiarism detection service, turnitin.com, to teach better techniques of conducting research and source documentation. Syllabus content, referrals to the University Writing Center, peer review, lecture, and examples of good and bad acknowledgement practice, as well as the professor's own use of the service, are techniques employed to turn the submission of papers to turnitin.com into a learning event, rather than into apresumption of guilt and possible punishment. Data show that most students seem to appreciate the approach taken.