StrikePlagiarism is a machine learning-based text recognition system designed to detect, prevent and manage plagiarism:
The sources used are:
- Open sources from the internet and databases from universities or publishing houses.
- RefBooks database. RefBooks is the scientific data base from Plagiat.pl that contains millions of doctoral theses, student articles, scientific magazines and other types of documents in more than 30 languages. This database also includes documents published on Scopus, Web *of *Science, *Springer, *EBSCO, etc.
IMPORTANT:
-
The anti-plagiarism systems help to detect plagiarism, but they cannot replace the work of the examiner.
-
Professors will analyse the report supplied by StrikePlagiarism.
-
Teachers will make the decision of labelling the work as plagiarism or not.
-
Students cannot use the anti-plagiarism system.
Anti-plagiarism system user manual PDF Video
Manual for interpreting the anti-plagiarism system similarity report PDF Video FAQ (in English)
Some considerations that must be taken into account before sending the file to analyse:
- The file size must be maximum 100MB. If the document to analyse exceeds this size, it must be separated into various documents.
- The file formats accepted by the web portal are: txt, *doc, *docx, pdf, *xls, *xlsx, *ppt, *pptx, *rtf, HTML, *htm, i *zip.
- The file format accepted by the anti-plagiarism system from the Aula Virtual are: txt, *doc, *docx, *odt, pdf, i *rtf.
Any other file format will not be accepted by the system..
- Images, graphics and formulas without a text will not be analysed. However, if these images, graphics and formulas contain some sort of text, it will be analysed.
- Although the anti-plagiarism programme can analyse if the text has been generated by Artificial Intelligence, it is not recommended to use this option since the results can be inaccurate
Access to the platform: https://antiplagio.uv.es
