1.paperyy and HowNet have different calculation methods.
Paperyy adopts semantic recognition technology based on deep learning, which can accurately identify the similarity of papers. HowNet duplicate checking is a traditional way, which mainly includes typesetting, word segmentation, duplicate removal, similarity calculation and so on. This method is easily deceived by simple text changes.
2.paperyy is more accurate, and parameters can be adjusted according to different needs.
Because paperyy uses the method of deep learning, it has higher accuracy in detecting plagiarism. At the same time, paperyy also supports functions such as custom weight and custom detection range to meet individual needs.
3. There is a risk of loopholes in HowNet duplicate checking.
The algorithm of HowNet duplicate checking is mainly aimed at text comparison, which is easy to be deceived by simple text modification such as smearing and replacement. In addition, it is not easy to identify pictures, charts and formulas when checking duplicate, which may cause errors.
4.paperyy has moderate price and high reliability.
Compared with other test software, paperyy has moderate price and high precision. Due to the adoption of deep learning technology, it can cope with the deformation and copying of most texts, thus ensuring the reliability of detection.
In addition, even if the paperyy is used for testing, the possibility of plagiarism cannot be completely ruled out. Therefore, in the process of writing, we should pay attention to maintaining academic integrity, consult relevant documents in time, and avoid too many similarities as much as possible. In addition, the similarity of papers can be effectively reduced and the quality and value of works can be improved by citing and indicating the source reasonably.
To sum up, there are huge differences between paperyy and HowNet in calculation method, accuracy, vulnerability risk and price. Considering that plagiarism is a problem involving academic ethics and academic norms, it is suggested to choose paperyy with high accuracy for detection.