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2. Content similarity detection - Wikipedia

   en.wikipedia.org/wiki/Content_similarity_detection

   Citation-based plagiarism detection (CbPD) [26] relies on citation analysis, and is the only approach to plagiarism detection that does not rely on the textual similarity. [27] CbPD examines the citation and reference information in texts to identify similar patterns in the citation sequences. As such, this approach is suitable for scientific ...

3. Copyleaks - Wikipedia

   en.wikipedia.org/wiki/Copyleaks

   Copyleaks is a plagiarism detection platform that uses artificial intelligence (AI) to identify similar and identical content across various formats. [1] [2]Copyleaks was founded in 2015 by Alon Yamin and Yehonatan Bitton, software developers working with text analysis, AI, machine learning, and other cutting-edge technologies.

4. Turnitin - Wikipedia

   en.wikipedia.org/wiki/Turnitin

   Turnitin, LLC also runs the informational website plagiarism.org and offers a similar plagiarism-detection service for newspaper editors and book and magazine publishers called iThenticate. Other tools included with the Turnitin suite are GradeMark (online grading and corrective feedback) and PeerMark (student peer-review service).

5. Comparison of anti-plagiarism software - Wikipedia

   en.wikipedia.org/wiki/Comparison_of_anti...

   The following tables compare software used for plagiarism detection. General. Software Developer First public release Latest stable version License

6. Unicheck - Wikipedia

   en.wikipedia.org/wiki/Unicheck

   Unicheck (previously known as Unplag) is a cloud-based plagiarism detection software that finds similarities, citations and references in texts. Unicheck is primarily used in K-12 and higher education, and is utilised by more than 400 institutions worldwide. The tool is also used as a stand-alone checker by individual users like writers ...

7. Grammarly - Wikipedia

   en.wikipedia.org/wiki/Grammarly

   In 2019, Grammarly added a tone detector to its writing assistant. This tool uses set rules and machine-learning to help users gauge the character of their writing and tailor it to a particular audience. [12] [13] That same year, the company held a second funding round, raising $90 million. [10]