Active Elicitation of Data for Word AlignmentInstitute for Software Research
Date of Original Version1-1-2010
Rights ManagementAll Rights Reserved
Abstract or DescriptionSemi-supervised word alignment aims to improve the accuracy of automatic word alignment by incorporating full or partial manual alignments. Motivated by standard active learning query sampling frameworks like uncertainty-, margin- and query-by-committee sampling we propose multiple query strategies for the alignment link selection task. Our experiments show that by active selection of uncertain and informative links, we reduce the overall manual effort involved in elicitation of alignment link data for training a semisupervised word aligner.
Citation InformationVamshi Ambati, Stephan Vogel and Jaime G. Carbonell. "Active Elicitation of Data for Word Alignment" (2010)
Available at: http://works.bepress.com/jaime_carbonell/1/