From Wikipedia, the free encyclopedia
Jump to navigation Jump to search
Unicheck logo 2.jpg
Unicheck logo
Type of site
Plagiarism and Similar Content Checker
Current statusActive

Unicheck (ex.Unplag) is a cloud-based plagiarism detection software that finds similarities, citations and references in a set of text.[1] In 2017, Unplag was rebranded as Unicheck.[2] The company is based in Kyiv, Ukraine.

Unicheck is primarily used in K-12 and higher education, counting more than 400 institutions worldwide.[3] The tool is also used as a stand-alone checker by individual users like writers, editors, bloggers, lawyers.[4]


Unicheck (Unplag at that time) was launched in 2014.[5] In 2016 Unicheck partnered with XСulture project and became Certified Partner with Canvas learning management system by Instructure [6] (in 2017 it gained a status of Canvas Alliance Partner[7]). It has also joined the FERPA act. Unicheck was rebranded in 2017. In the summer of 2017, Unicheck became the first plagiarism checker to integrate with Google Classroom.[8] It has also released a new type of integration with Canvas, called “native” and based on both LTI and API. After that in January 2018 Unicheck released Add-on for Google Docs.[9]

In 2017 Unicheck’s basic features became available for free in the following countries: US, UK, Canada, Australia, New Zealand, Ireland, Malta, and South Africa.


Unicheck offers similarities, citations, and references search and recognition in the texts. It can also discover characters that have been replaced in the text from another alphabet. For example, similar characters from Cyrillic and Latin alphabets. To find similarities and paraphrase, checks are performed against the Internet (web pages indexed by Yahoo and Google), open source repositories, and user’s internal library or database. The check results are presented in similarity report, where each of the similarity that has been found has a link to the source. These reports can be downloaded in a PDF document.

Unicheck can be used as a stand-alone online tool, or integrated into LMS (Learning Management System) via plugin, LTI, API or LTI+API types of integrations.

Unicheck is compatible with the following file formats: .doc, .docx, .rtf, .txt, .odt, .ppt, .pptx, .html, .pdf, .pages, .gdoc, as well as rar and zip archives, and files uploaded from Google Drive, oneDrive, Dropbox.[10] Unicheck allows to store documents in users’ internal library. Global settings allow to configure check sensitivity and if users want to share their checked documents with Unicheck’s database.[10] Each newly signed up user receives 5 trial pages.


Unicheck uses an algorithm that searches for similar text on web pages, in open source repositories, and internal library. Accuracy of searches is achieved by using the algorithm that divides text into small shifting sequences and uses them to look for similarities and by using live web index, which enables checks against all web pages.[11]

The technology was developed by computer science engineers and professors. In 2017, the technology was improved by adding NLP (Natural Language Processing) principles. This enabled the system to recognize synonyms and find paraphrased content in the checked text. The algorithm has been compared to latent semantic indexing, a method used by Google to determine connections between words and phrases.[12]

The technology can recognize citations and references in the text, given they are properly formatted according to any of the academic styles. Currently, the technology recognizes APA, MLA, Chicago, Turabian, and Harvard styles. The speed of checks per page is 4 seconds.


Unicheck has developed the following types of integrations with Learning Management Systems (LMS):


Plugin type of integration is characterized by enriching the LMS functionality with added features of the tool, without changing native interface. This type of integration is used with Moodle and Sakai LMS.


LTI integration is characterized by a completely new interface created within the LMS to enable Unicheck’s functions. Unicheck developed this type of integrations for Canvas, Moodle, Schoology, Blackboard, and NEO LMS.


When this type of integration is used, the two systems, that of LMS and Unicheck, are connected by API to ensure their interaction. API works through determining the functionality of the system, at the same time disregarding the way that functionality is realized. Thanks to this type of interaction, Unicheck integrates with Google Classroom.


This is a special type of integration that takes principles of both API and LTI to create a native integration, that is presenting Unicheck’s functions in the native interface of LMS. This type of integration is only available for Canvas LMS.

See also[edit]


  1. ^ Azam, Muhammad (31 July 2015). "Startup Blog: What Basics You Should Know". Business2Community. Retrieved 3 August 2015.
  2. ^ https://unicheck.com/blog/unplag-is-now-unicheck
  3. ^ https://talentapestry.com/how-it-works-client/plagiarism-free-promise/
  4. ^ Huffman, Justin (7 August 2015). "How Lawyers Fight Plagiarism". Guardian Liberty Voice. Retrieved 7 August 2015.
  5. ^ "Unicheck profile". Crunch Base. Retrieved 3 August 2015.
  6. ^ korzh, Alisa. "Unicheck Launches Deep Integration With Canvas LMS - eLearning Industry". eLearning Industry. Retrieved 2017-11-03.
  7. ^ "Alliance Partner - Unicheck | Canvas Community". community.canvaslms.com. Retrieved 2017-11-03.
  8. ^ "Plagiarism Checker Unicheck And Google Classroom Integration". Unicheck Blog. 2017-06-23. Retrieved 2017-11-03.
  9. ^ "Unicheck Similarity Checker Add-On for Google Docs". Unicheck Blog. 2018-02-09. Retrieved 2018-03-01.
  10. ^ a b Horvath, Brian (24 August 2015). "Get Higher Content Quality With These Three Tools". Business 2 Community. Retrieved 26 August 2015.
  11. ^ Marchenko, Oleksandr; Anisimov, Anatoly; Nykonenko, Andrii; Rossada, Tetiana; Melnikov, Egor (2017-06-21). "Authorship Attribution System". Natural Language Processing and Information Systems. Lecture Notes in Computer Science. Springer, Cham: 227–231. doi:10.1007/978-3-319-59569-6_27. ISBN 9783319595689.
  12. ^ Marchenko, Oleksandr; Anisimov, Anatoly; Nykonenko, Andrii; Rossada, Tetiana; Melnikov, Egor (2017-06-21). "Machine Learning Method for Paraphrase Identification". Flexible Query Answering Systems. Lecture Notes in Computer Science. Springer, Cham: 164–173. doi:10.1007/978-3-319-59692-1_14. ISBN 9783319596914.

External links[edit]