Joint Inference for Fine-grained Opinion Extraction
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Cites background from "Joint Inference for Fine-grained Op..."
...Word sequence and tree structure are known to be complementary information for extracting relations....
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Cites background from "Joint Inference for Fine-grained Op..."
...…as a two-tier problem: first a piece of text is marked as either objective or subjective, and then only the subjective text is assessed to determine whether it is positive, negative, or neutral (Wiebe, Wilson, & Cardie, 2005; Choi & Cardie, 2010; Johansson & Moschitti, 2013; Yang & Cardie, 2013)....
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References
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"Joint Inference for Fine-grained Op..." refers methods in this paper
...We formulate the task of opinion entity identification as a sequence labeling problem and employ conditional random fields (CRFs) (Lafferty et al., 2001) to learn the probability of a sequence assignment y for a given sentence x....
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7,848 citations
"Joint Inference for Fine-grained Op..." refers methods in this paper
...We trained the classifiers for relation extraction using L1-regularized logistic regression with default parameters using the LIBLINEAR (Fan et al., 2008) package....
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7,452 citations
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