Modeling Perspective Using Adaptor Grammars

Strong indications of perspective can often come from collocations of arbitrary length; for example, someone writing get the government out of my X is typically expressing a conservative rather than progressive viewpoint. However, going beyond unigram or bigram features in perspective classification gives rise to problems of data sparsity. We address this problem using nonparametric Bayesian modeling, specifically adaptor grammars (Johnson et al., 2006). We demonstrate that an adaptive na

• Type: Journal
• Year: 2010
• Where: EMNLP
• Authors: Eric Hardisty, Jordan L. Boyd-Graber, Philip Resnik
• Keywords: EMNLP 2010, Multiword Lexical Usages, Natural Language Processing, Nonparametric Bayesian Modeling, Perspective Classification