Automatic Elements Extraction of Chinese Web News Using Prior Information of Content and Structure

We propose a set of efficient processes for extracting all four elements of Chinese news web pages, namely news title, release date, news source and the main text. Our approach is based on a deep analysis of content and structure features of current Chinese news. We take content indicators as the key to recover tree structure of the main text. Additionally, we come up with the concept of Length-Distance Ratio to help improve performance. Our method rarely depends on selection of samples and has strong generalization ability regardless of training process, distinguishing itself from most existing methods. We have tested our approach on 1721 labeled Chinese news pages from 429 web sites. Results show that an 87% accuracy was achieved for news source extraction, and over 95% accuracy for other three elements.