First of all, from the point of view of algorithm, some systems adopt the algorithm based on text matching, and judge whether there is plagiarism by comparing the text similarity of two papers. These systems usually use word frequency, word vector and semantic analysis to calculate the similarity between papers.

Secondly, some systems adopt algorithms based on fingerprint and feature extraction. These systems judge whether there is plagiarism by calculating the unique characteristics of papers, such as the frequency, distance and order of words and phrases. This method can effectively detect plagiarism by simply modifying the paper or replacing the text.

In addition, some systems use hybrid algorithms, combining text matching and feature extraction. These systems usually combine various algorithms and technologies to improve the accuracy and reliability of paper duplicate checking.

In addition to the differences in algorithm, different paper duplicate checking systems are different in function and performance. Some systems provide simple text comparison function, and users can compare two papers to detect similarities. Other systems provide more complex functions, such as batch detection, automatic report generation and repeated database checking.

In addition, different systems have different performance characteristics. Some systems have the characteristics of fast processing speed and high accuracy, and can detect a large number of papers in a short time. However, other systems may have slow processing speed, and some text modification technologies and plagiarism technologies may have unsatisfactory detection results.