Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Local adaptive extraction of references
KI'10 Proceedings of the 33rd annual German conference on Advances in artificial intelligence
Hi-index | 0.00 |
Information extraction (IE) is a form of shallow text understanding that locates specific pieces of data in natural language documents. Although automated IE systems began to be developed using machine learning techniques recently, the performances of those IE systems still need to be improved. This paper describes an information extraction system based on transformation-based learning, which uses learned meta-rules on patterns for slots. We plan to empirically show these techniques improve the performance of the underlying information extraction system by running experiments on a corpus of IT resumé documents collected from Internet newsgroups.