Paper: Automatic Food Categorization from Large Unlabeled Corpora and Its Impact on Relation Extraction

ACL ID E14-1071
Title Automatic Food Categorization from Large Unlabeled Corpora and Its Impact on Relation Extraction
Venue Annual Meeting of The European Chapter of The Association of Computational Linguistics
Session Main Conference
Year 2014
Authors

We present a weakly-supervised induc- tion method to assign semantic informa- tion to food items. We consider two tasks of categorizations being food-type classi- fication and the distinction of whether a food item is composite or not. The cate- gorizations are induced by a graph-based algorithm applied on a large unlabeled domain-specific corpus. We show that the usage of a domain-specific corpus is vi- tal. We do not only outperform a manually designed open-domain ontology but also prove the usefulness of these categoriza- tions in relation extraction, outperforming state-of-the-art features that include syn- tactic information and Brown clustering.