Categorization Extraction Algorithm for Scientific-Related News on Websites
There are a lot of non-scientific-related news on Websites. In order to improve the useful value for the news information,a novel multilevel dichotomous model of text automatic categorization extraction system for technology news based on TF-IDF was designed and implemented. The news offered by government news website and Phoenix as the research background in scientific news categorization extraction. Experiments showed a85. 3 percent accuracy for scientific-related news and 82. 9 percent recognition rate for nonscientific-related news respectively in the test containing two hundred thousand documents and more than four thousand news classifications. The results showed that the proposed method offered a useful reference model on website scientific intelligence.