Database-Text Alignment via Structured Multilabel Classification

By Benjamin Snyder, Regina Barzilay. 2007

42 citations recorded by the source corpus.

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Citations in the corpus

Learning Semantic Correspondences with Less Supervision (2009, methodology): “Graph matching and multilabel are supervised results reported in Snyder and Barzilay (2007).”
Learning to Interpret Natural Language Navigation Instructions from Observations (2011, methodology): “Various approaches have been used including supervised training (Snyder and Barzilay 2007), iteratively retraining a semantic parser/language generator to disambiguate the context (Kate and Mooney 2007; Chen, Kim, and Mooney 2010), building a generative model of the content selection process…”
Training a Multilingual Sportscaster: Using Perceptual Context to Learn Language (2014, methodology): “However, Snyder and Barzilay (2007) use a supervised approach that requires annotating the correct correspondences between the text and the semantic representations.”
Individual and Domain Adaptation in Sentence Planning for Dialogue (2007, methodology): “…to address this limitation by investigating techniques for learning a generation dictionary automatically from different types of corpora, such 448 Individual and Domain Adaptation in Dialogue as user reviews (Barzilay & Lee, 2002; Higashinaka, Walker, & Prasad, 2007; Snyder & Barzilay, 2007).”
Multi-Resolution Language Grounding with Weak Supervision (2014, methodology): “Early semantic parsing work made use of fully supervised training (Zettlemoyer and Collins, 2005; Ge and Mooney, 2006; Snyder and Barzilay, 2007), but more recent work has focused on reducing the amount of supervision required (Artzi and Zettlemoyer, 2013).”
Label Ranking under Ambiguous Supervision for Learning Semantic Correspondences (2010, background): “The set of records, which we call the candidate set, is gathered via a cheap automatic process which introduces noise and ambiguity in the supervision.”
A systematic analysis of performance measures for classification tasks (2009, background): “Examples include classification of functions of yeast genes (Mewes, Albermann, Heumann, Lieb, & Pfeiffer, 1997), identifying scenes from image data (Li, Zhang, & Zhu, 2006) or text-database alignment and word alignment in machine translation (Snyder & Barzilay, 2007).”