Predicting the Structure of Cooking Recipes

نویسندگان

  • Jermsak Jermsurawong
  • Nizar Habash
چکیده

Cooking recipes exist in abundance; but due to their unstructured text format, they are hard to study quantitatively beyond treating them as simple bags of words. In this paper, we propose an ingredientinstruction dependency tree data structure to represent recipes. The proposed representation allows for more refined comparison of recipes and recipe-parts, and is a step towards semantic representation of recipes. Furthermore, we build a parser that maps recipes into the proposed representation. The parser’s edge prediction accuracy of 93.5% improves over a strong baseline of 85.7% (54.5% error reduction).

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تاریخ انتشار 2015