According to this logical thinking, there are only a handful of detection systems that can meet the requirements in China. Friends who know this information will know that there are only three companies, because these three companies are the only ones with authority to collect all kinds of academic resources in China, and they are also the first to study the text comparison detection mechanism. In fact, many university libraries provide paper database resources for faculty and students, namely, China HowNet, VIP and Wanfang.
Let's first introduce the VIP Tongda academic paper detection expert system based on "massive database" and "advanced detection mechanism", but China Knowledge Network and Wanfang will not mention it, because VIP has been paying attention to and participating in this detection system, so it's a bit of a say.
First of all, from the perspective of "massive database", Wipton Tongda Academic Paper Detection Expert System is another anti-plagiarism detection system supported by massive periodical literature system after China HowNet and Wanfang, and it has a powerful comparison database system. The database is divided into four aspects, covering a wide range of paper text data: 1, VIP professional database-the largest and most comprehensive full-text database of Chinese sci-tech journals in China, with more than 26.7 million full-text documents at present. 2. Network resources-Monitor the billions of web pages collected by Google and update them every week. 3.Tonda*** likes this database very much-it contains more than 2 million papers from various colleges and research institutions and is updated every week. 4. User-built library-to meet the specific needs of users. The meaning of user-built library is not explained here, but will be introduced in detail when introducing the system functions later.
The concept of "advanced detection mechanism" is more professional. Wipton Tongda's academic paper detection expert system adopts "text fingerprint identification technology", which can accurately hit the text target without over-detection. But to explain clearly why this detection mechanism can do this, we need to give an example and use an ordinary sentence as a blue book to explain. Our daily written language must be organized by subjects and predicates, and modified by some adjectives, such as the sentence "I type fast". The contribution of each word in this sentence structure is different, such as the subject "I" and the predicate "Da". These two words have made great contributions. If we change these two words, the whole meaning of this sentence will change. However, the words "Zheng" and "Fei Fei" do not contribute much. If you change the overall meaning of these two words, it will not be ruined. "You read fast" and "I type fast now". From these two modified sentences, we can see the importance of word contribution. We also call this feature the fingerprint of the text. Wipton's expert system for detecting academic papers uses the concept of word contribution to capture unchangeable keywords in the text as the basis for comparing sentence differences. Using this technology, it can not only achieve accurate hit, but also cause excessive detection. Now you should understand why I keep mentioning the importance of the detection mechanism used in the paper detection system.
Well, some basic technical advantages of Wipton academic paper detection expert system should be made clear, which is why this system can provide users with a good experience base. Of course, having these basic things is not enough to illustrate the advantages of the system. Later, from the perspective of using the operation itself, the function of the system will be discussed, so that everyone can use it better. Of course, the function of the self-built library will be explained in detail, because this function is not available in other detection systems currently running on the market.