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Coupled semi-supervised learning for information extraction
2010
Proceedings of the third ACM international conference on Web search and data mining - WSDM '10
We consider the problem of semi-supervised learning to extract categories (e.g., academic fields, athletes) and relations (e.g., PlaysSport(athlete, sport)) from web pages, starting with a handful of labeled training examples of each category or relation, plus hundreds of millions of unlabeled web documents. Semi-supervised training using only a few labeled examples is typically unreliable because the learning task is underconstrained. This paper pursues the thesis that much greater accuracy
doi:10.1145/1718487.1718501
dblp:conf/wsdm/CarlsonBWHM10
fatcat:wiecoon73bbffkjvkzlxqbn2ky