English Article Style Recognition and Matching by Using Web Semantics

With the explosion of internet information, people feel helpless and difficult to choose in face massive information. However, traditional method organize a huge set original documents is not only time-consuming laborious, but also ideal. The automatic text classification can liberate users from tedious document processing work, recognize distinguish different contents more conveniently, make large number complicated institutionalized systematized, greatly improve utilization rate This paper adopts termed-based model extract features web semantics represent document. extracted are used learn reduced support vector machine. experimental results show that proposed correctly identify most writing styles.