Research on English Text Information Filtering Algorithm Based on SVM
Jing Ouyang · 2020 IEEE International Conference on Power, Intelligent Computing and Systems (ICPICS) · 2020
In terms of the current international situation, English is still the most widely used language interoperability many countries. Many people use English as a second language, and even some large international companies, who store their important documents in English, so research in the English language is needed, and one of the most significant research is the English text information filtering algorithm. As we all know, text information filtering is a kind of text information processing technology, including information classification, filtering and other technologies which is the link between text information and computer processing and filtering technology, and can be reprocessed according to the information content of the text. In the process of information processing, support vector machines (SVM) can solve many problems in the process. Generally, the problems such as high sparse dimension of text vector, high correlation between information features, and high sparsity among vectors always exist in text information filtering, while SVM can exactly solve the above problems. According to the feature of SVM for text problems, the center set region is established for positive sample clustering when filtering information, and it is difficult to judge the data and continue to use clustering decision when meeting later, so the accuracy of SVM algorithm in information filtering is improved.