The message has been sent successfully The most powerful text plagiarism detection system
More convenient, faster, and more accurate, thanks to artificial intelligence.
Such a system allows you to determine which fragments of the document have already been used in other sources.
Plagiarism is the theft of other people's ideas or texts without permission, which is contrary to ethics, morality and the law.
The systems help to detect plagiarism in order to punish plagiarists and also help not to plagiarize yourself.
Rucont allows you to determine the originality of the analyzed document, highlight borrowed fragments, and make a list of sources.
Plagiarism is the theft of other people's ideas or texts without permission, which is contrary to ethics, morality and the law.
The systems help to detect plagiarism in order to punish plagiarists and also help not to plagiarize yourself.
Rucont allows you to determine the originality of the analyzed document, highlight borrowed fragments, and make a list of sources.
Educational and scientific institutions, publishing houses.
To graduate students, students, teachers, authors of articles, editors of journals.
To graduate students, students, teachers, authors of articles, editors of journals.
- The accuracy of the definition of borrowings, a simple and modern interface
- Artificial intelligence speeds up and simplifies work
- Detector of text generated by neural networks
- Superimposing a borrowed fragment on the one being checked clearly shows paraphrasing, the presence of synonyms, word permutations and translations
- Convenient verification report in PDF format
- An index database based on direct licensing agreements with publishers and open Internet publications
3074 documents checked in 24 hours
139 attempts to cheat the system were detected in 24 hours
2097293202 sources for detecting plagiarism
4816 number of direct license agreements with copyright holders
Getting started
Uploading a document and viewing
Supported formats: .txt, .doc, .docx, .pdf, .rtf, .odt.
After downloading and checking, a detailed view of the results will be available.
Features
Reports
All checks can be exported into a summary or detailed PDF report.Snippet
A special snippet will clearly show the source of borrowing and help to quickly and correctly identify it.Different Languages
We recognize borrowings even from sources in other languages.Classification of text fragments
The expert can change the type of borrowing using the borrowing classification tool, defining the borrowing as: borrowing, quoting, author's work (self-citation), or exclude a fragment from consideration.Index databases
The index database is a specially formed structure based on the original search indexes of text and graphic works. When working with the RUKONTEXT system and its index database, the original original text works are not stored, transmitted, or reproduced either in full or in part; the borrowed fragments are quoted with a link to the source and authorship in accordance with current legislation.
RUCONTEXT uses the following index databases:
RUCONTEXT uses the following index databases:
Indexes of scientific journals
Scientific and industry journals of open access, including those from the list of the Higher Attestation Commission, with scientific articlesIndexes of media publications
Mass media of various profiles: political, technical, economic, sociological, legal, managerial, accounting, historical and othersIndexes of archives of state organizations
Official archives of state organizations, including the archive of the Higher Attestation Commission
Indexes of patent information
Patents of Russia and the USSR, foreign countries, including patent claims of inventions, utility models, industrial designs
Indexes of abstracts and reference books
Abstracts in various fields, reference books, dictionaries, encyclopedias and other open sources containing specialized scientific and scientific-technical information
contains at least 1.2 million document indexes:
• indexes of abstracts and dissertations defended in the USSR and the Russian Federation since 1969;• indexes of dissertations of the USA, European countries, South American countries;
• indexes of dissertations of the CIS countries;
DB registration certificate № 2024670051 from 04.09.2024
contains at least 60 million document indexes:
• indexes of scientific articles and issues of periodicals from the list of the Higher Attestation Commission;• indexes of open scientific resources of Russia, CIS, Europe, USA, South America;
• indexes of industry and scientific journals in Russia and CIS countries;
• indexes of conferences, scientific reports, research and development reports
DB registration certificate № 2024670050 from 03.09.2024
contains at least 64 million document indexes:
• indexes of the Codex database• indexes of the Garant database
contains at least 660 thousand document indexes:
• educational publications issued by a significant number of Russian educational literature publishers;• educational literature published in the last 10 years, and in the disciplines of the basic part of the humanitarian, social and economic cycle — in the last 5 years;
DB registration certificate № 2024670057 from 08.11.2024
Frequent questions
Rucont was created and maintained by a group of companies with a history of more than 55 years in the market.
Among them:
However, already in 2016, the approach was considered unpromising, and a second version based on linguistic text analysis was introduced. In 2020, neural networks will be implemented in some parts of the system.
Since the beginning of 2022, the system has been completely switched to artificial intelligence.
Among them:
- Agency for the distribution of foreign publications – more than 55 years
- The Book-Service Agency has been operating for more than 30 years
- The Central collector of Bibcom libraries has been working for more than 20 years
- Publishing house "Soviet Sport" - more than 25 years
- National Digital Resource "RUCONT" - more than 10 years
However, already in 2016, the approach was considered unpromising, and a second version based on linguistic text analysis was introduced. In 2020, neural networks will be implemented in some parts of the system.
Since the beginning of 2022, the system has been completely switched to artificial intelligence.
Our clients
St. Petersburg State University
Ural Federal University
National Research Nuclear University
St. Petersburg State Maritime Technical University
All-Russian Scientific Research Institute of Phytopathology
Irkutsk National Research Technical University
Russian University of Technology MIREA
St. Petersburg State University of Architecture and Civil Engineering
Kazan State Energy University
Tomsk State University of Architecture and Civil Engineering
All-Russian Research Institute for the Operation of Nuclear Power Plants
Moscow Aviation Institute
more than 150 regular customers
Any other questions?
If you have any question, wish, complaint or suggestion, write to us.
