Automatic web news extraction using tree edit distance
Proceedings of the 13th international conference on World Wide Web
Template-independent news extraction based on visual consistency
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
A unified approach for extracting multiple news attributes from news pages
PRICAI'10 Proceedings of the 11th Pacific Rim international conference on Trends in artificial intelligence
An automatic web news article contents extraction system based on RSS feeds
Journal of Web Engineering
An efficient language-independent method to extract content from news webpages
Proceedings of the 11th ACM symposium on Document engineering
News information extraction based on adaptive weighting using unsupervised Bayesian algorithm
WISM'11 Proceedings of the 2011 international conference on Web information systems and mining - Volume Part II
Extracting multiple news attributes based on visual features
Journal of Intelligent Information Systems
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We consider the problem of template-independent news extraction. The state-of-the-art news extraction method is based on template-level wrapper induction, which has two serious limitations. 1) It cannot correctly extract pages belonging to an unseen template until the wrapper for that template has been generated. 2) It is costly to maintain up-to-date wrappers for hundreds of websites, because any change of a template may lead to the invalidation of the corresponding wrapper. In this paper we formalize news extraction as a machine learning problem and learn a template-independent wrapper using a very small number of labeled news pages from a single site. Novel features dedicated to news titles and bodies are developed respectively. Correlations between the news title and the news body are exploited. Our template-independent wrapper can extract news pages from different sites regardless of templates. In experiments, a wrapper is learned from 40 pages from a single news site. It achieved 98.1% accuracy over 3,973 news pages from 12 news sites.