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StrikePlagiarism is a machine learning text recognition system designed to detect, prevent and manage plagiarism:

The sources used are:

- Open sources from the Internet and databases from universities and publishers.

- RefBooks database. RefBooks is Plagiat.pl's scientific database containing millions of PhD theses, publications, student articles, scientific journals and other types of documents in more than 30 languages. This database also includes documents published in Scopus, Web of Science, Springer, EBSCO, etc.

IMPORTANT:

1. Anti-plagiarism systems help detect plagiarism but are not a substitute for the examiner's work.
2. Teachers will perform the analysis of the report provided by StrikePlagiarism.
3. Teachers make the decision to grade a work as plagiarism or not.

Anti-plagiarism system user manual PDF Video

Manual for interpreting the similarity report of the anti-plagiarism system PDF Video FAQ (in English)

Some considerations to take into account when sending files for analysis:

- The file size must be at most 100MB. If the document to be analyzed exceeds this size, it must be divided into several documents.

- The file formats accepted from the web portal are: txt, doc, docx, pdf, xls, xlsx, ppt, pptx, rtf, html, htm, and zip.

- The file formats accepted by the anti-plagiarism system from the Virtual Classroom are: txt, doc, docx, odt, pdf, and rtf.

Any other file format will not be accepted by the system.

- Images, graphics, and formulas that do not contain any text will not be analyzed. However, if these images, graphics, and formulas contain any text, it will be analyzed.

-Although the anti-plagiarism program can analyze whether the text has been generated by an Artificial Intelligence, the use of this option is not recommended since the results may not be accurate.

Access to the platform: https://antiplagio.uv.es