Plagiarism detection

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

Plagiarism detection in Chinese based on chunk and paragraph weight

Abstract: Aiming at the Chinese academic paper plagiarism detection, proposed chunk based plagiarism detection algorithm with chunk extraction method based on character or word. Taken account of that different part of document has different importance, proposed two paragraph weight algorithms and defined three paragraph weight functions. The best chunk lengths are determined by experiments. Experiments show that using paragraph weight can enhance the detection effect.

Shape-Based Plagiarism Detection for Flowchart Figures in Texts

Abstract: Plagiarism detection is well known phenomenon in the academic arena. Copying other people is considered as serious offence that needs to be checked. There are many plagiarism detection systems such as turn-it-in that has been developed to provide this checks. Most, if not all, discard the figures and charts before checking for plagiarism. Discarding the figures and charts results in look holes that people can take advantage. That means people can plagiarized figures and charts easily without the current plagiarism systems detecting it. There are very few papers which talks about flowcharts plagiarism detection. Therefore, there is a need to develop a system that will detect plagiarism in figures and charts. This paper presents a method for detecting flow chart figure plagiarism based on shape-based image processing and multimedia retrieval. The method managed to retrieve flowcharts with ranked similarity according to different matching sets.

On the development of a plagiarism detection model based on citation analysis using a bibliographic database

Abstract: A relatively new method for the detection of text plagiarism is proposed based on a search for original sources with an identical or similar list of references. First of all, this is applied to the most difficult to detect forms of translated plagiarism and the plagiarism of ideas. This method successfully proved itself in test studies of groups of foreign authors and is a continuation of our studies. The peculiarity of the approach that is proposed by the authors is the use of multidisciplinary bibliographic databases rather than full-text databases, which are often unavailable due to the high price of subscriptions under Russian conditions. The advantage of their use is the access to the maximum possible number of article references, which significantly extends the base for the search for originals while analyzing suspicious scientific publications. The step-by-step algorithm for addressing a query to the Web of Science and Scopus databases and analysis of the obtained data can be recommended for implementation into systems of plagiarism detection as an additional component.

A Search of Verilog Code Plagiarism Detection Method

Abstract: In order to detect the plagiarism in Verilog codes of CPU design experiment, the existing code detection technologies are studied, and a Verilog code plagiarism detection combining the MOSS system and abstract grammar tree model (AST) is proposed This method first verifies the Verilog code's executable and correctness, then filters the suspected plagiarism code through the MOSS system, then filters the suspected plagiarism code by the AST-based code detection method, the sum of the two filtered files is the final result This method can detect both similarity of texts and similarity of structure And the latter can make progress for detecting the program plagiarism that changes the code structure

Graph-based Approach to Text Alignment for Plagiarism Detection in Persian Documents.

Abstract: This paper presents a new approach for Persian plagiarism detection. This approach uses a graph structure as well as one of the graph similarity methods (iterative methods) for similarity detection of two Persian documents. In this approach, documents are represented by a graph with specified length, then each part of suspicious document is compared to that of the source document. The graph is made if these parts have more common bigrams than a predefined threshold. Once graphs are made, an iterative method is used to find analogous nodes in graphs. Two graphs are marked as similar if they contain at least a certain number of similar nodes. In order to evaluate the proposed method, it was run on PAN2015 and PAN2016 Persian Text Alignment dataset. The Plagdet score is defined to evaluate plagiarism detection methods in PAN contest. The gained Plagdet of proposed method is 90% on PAN2015 and 87% on PAN2016. CCS Concepts • Information systems➝ Plagiarism Detection software • Computing methodologies➝ Graph-based