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Intimate Learning: A Novel Approach for Combining Labelled and Unlabelled Data
2005
International Joint Conference on Artificial Intelligence
This paper introduces a new bootstrapping method closely related to co-training and scoped-learning. The method is tested on a Web information extraction task of learning course names from web pages in which we use very few labelled items as seed data (10 web pages) and combine with an unlabelled set (174 web pages). The overall performance improved the precision/recall from 3.11%/0.31% for a baseline EM-based method to 44.7%/44.1% for intimate learning.
dblp:conf/ijcai/ShiS05
fatcat:dydi6hevv5dunmjqrmhmfnnoay