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Active Learning Selection Strategies for Information Extraction  (Make Corrections)  
Aidan Finn Nicholas Kushmerick Smart Media Institute, Computer Science...



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Abstract: The need for labeled documents is a key bottleneck in adaptive information extraction. One way to solve this problem is through active learning algorithms that require users to label only the most informative documents. We investigate several document selection strategies that are particularly relevant to information extraction. We show that some strategies are biased toward recall, while others are biased toward precision, but it is difficult to ensure both high recall and precision. We also... (Update)

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BibTeX entry:   (Update)

@misc{ nicholas-active,
  author = "Aidan Finn Nicholas",
  title = "Active Learning Selection Strategies for Information Extraction",
  url = "citeseer.ist.psu.edu/733683.html" }
Citations (may not include all citations):
91   Improving generalization with active learning - Cohn, Atlas et al. - 1994
75   Heterogeneous uncertainty sampling for supervised learning - Lewis, Catlett - 1994
70   Relational learning of patternmatch rules for information ex.. - Califf, Mooney - 1999
46   Adaptive information extraction from text by rule induction .. (context) - Ciravegna - 2001
46   Machine Learning for Information Extraction in Informal Doma.. - Freitag - 1998
45   Committee-based sampling for training probabilistic classifi.. - Dagan, Engelson - 1995
43   Boosted wrapper induction - Freitag, Kushmerick - 2000
17   Toward general-purpose learning for information extraction - Freitag - 1998
8   Active learning of partially hidden Markov models - Scheffer, Wrobel - 2001
8   Usersystem cooperation in document annotation based on infor.. - Ciravegna, Dingli et al. - 2002
4   Active learning for natural language processing and informat.. (context) - Thompson, Califf et al. - 1999
4   Timely and non-intrusive active document annotation via adap.. - Ciravegna, Dingli et al. - 2002
4   Selective sampling with reduntant views (context) - Muslea, Minton et al. - 2000

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