A sequential algorithm for training text classifiers
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Improving Generalization with Active Learning
Machine Learning - Special issue on structured connectionist systems
A re-examination of text categorization methods
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Machine learning in automated text categorization
ACM Computing Surveys (CSUR)
Constructing informative prior distributions from domain knowledge in text classification
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
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Active learning efficiently hones in on the decision boundary between relevant and irrelevant documents, but in the process can miss entire clusters of relevant documents, yielding classifiers with low recall. In this paper, we propose a method to increase active learning recall by constraining sampling to a document subset rich in relevant examples.