@article{Craven:2000,
  abstract = {The World Wide Web is a vast source of information accessible to computers, but understandable only to humans. The goal of the research described here is to automatically create a computer understandable knowledge base whose content mirrors that of the World Wide Web. Such a knowledge base would enable much more effective retrieval of Web information, and promote new uses of the Web to support knowledge-based inference and problem solving. Our approach is to develop a trainable information extraction system that takes two inputs. The first is an ontology that defines the classes (e.g., company, person, employee, product) and relations (e.g., employed by, produced by) of interest when creating the knowledge base...},
  added-at = {2007-12-14T02:37:50.000+0100},
  author = {Craven, Mark and DiPasquo, Dan and Freitag, Dayne and McCallum, Andrew and Mitchell, Tom and Nigam, Kamal and Slattery, Se\'{a}n},
  biburl = {http://www.bibsonomy.org/bibtex/2edb8b670fb4dc8cdcebbbce2110149e0/diego_ma},
  interhash = {68683ddac8974e9b3867c4b076a2b52f},
  intrahash = {edb8b670fb4dc8cdcebbbce2110149e0},
  journal = {Artificial Intelligence},
  keywords = {web_data_extraction},
  timestamp = {2007-12-14T02:37:50.000+0100},
  title = {Learning to Construct Knowledge Bases from the World Wide Web},
  url = {http://citeseer.nj.nec.com/198786.html},
  year = 2000
}