Based on the multi-level rapid detection of digital fingerprints, the system performs designated digital fingerprint processing on each user who submits a paper, and then compares it with the papers in the relevant database, and obtains the similarity of the papers according to the comparison results.

Support a variety of paper types, the system supports digital fingerprint comparison from word to sentence and text level, can detect plagiarism from sentence to whole paper, and supports a variety of paper types.

With its powerful document analysis function, the paper duplicate checking system of HowNet can not only provide detailed similarity analysis reports of papers submitted by users, including text overlapping, similar positions and similar contents, but also accurately distinguish whether similar positions belong to plagiarism or citation.

To identify all kinds of academic misconduct, the system can not only identify traditional dominant factors such as plagiarism, but also identify hidden factors such as innovation, and provide a comprehensive duplicate check report.

Accurate and fast detection results, the system adopts efficient data flow algorithm and fast comparison algorithm, which can get accurate detection results in a short time.

The detection results are timely and accurate, and the paper duplicate checking system of HowNet controls the detection results accurately, which can meet the needs of different schools and institutions.

Strong technical support, the paper duplicate checking system of HowNet is based on a strong digital resource library and leading technical support, which ensures the accuracy and authority of the test results.