Selecting actions for resource-bounded information extraction using reinforcement learning

@inproceedings{Kanani2012SelectingAF,
  title={Selecting actions for resource-bounded information extraction using reinforcement learning},
  author={Pallika H. Kanani and Andrew McCallum},
  booktitle={WSDM},
  year={2012}
}
Given a database with missing or uncertain content, our goal is to correct and fill the database by extracting specific information from a large corpus such as the Web, and to do so under resource limitations. We formulate the information gathering task as a series of choices among alternative, resource-consuming actions and use reinforcement learning to select the best action at each time step. We use temporal difference q-learning method to train the function that selects these actions, and… CONTINUE READING
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