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» Machine Learning for Information Extraction
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ACL
2003
14 years 11 months ago
Using Predicate-Argument Structures for Information Extraction
In this paper we present a novel, customizable IE paradigm that takes advantage of predicate-argument structures. We also introduce a new way of automatically identifying predicat...
Mihai Surdeanu, Sanda M. Harabagiu, John Williams,...
CIKM
2006
Springer
15 years 1 months ago
Incorporating query difference for learning retrieval functions in world wide web search
We discuss information retrieval methods that aim at serving a diverse stream of user queries such as those submitted to commercial search engines. We propose methods that emphasi...
Hongyuan Zha, Zhaohui Zheng, Haoying Fu, Gordon Su...
ALT
2010
Springer
14 years 11 months ago
Bayesian Active Learning Using Arbitrary Binary Valued Queries
We explore a general Bayesian active learning setting, in which the learner can ask arbitrary yes/no questions. We derive upper and lower bounds on the expected number of queries r...
Liu Yang, Steve Hanneke, Jaime G. Carbonell
ICML
1995
IEEE
15 years 1 months ago
Learning Collection FUsion Strategies for Information Retrieval
In this paper we describe an Information Retrieval problem called collection fusion. The collection fusion problem is to maximize the number of relevant natural language documents...
Geoffrey G. Towell, Ellen M. Voorhees, Narendra Ku...
ICML
2009
IEEE
15 years 4 months ago
Learning linear dynamical systems without sequence information
Virtually all methods of learning dynamic systems from data start from the same basic assumption: that the learning algorithm will be provided with a sequence, or trajectory, of d...
Tzu-Kuo Huang, Jeff Schneider