"Comparable Recipes": A Construction and Analysis of a Dataset of Recipes Described by Different People for the Same Dish

Abstract

Recording high-quality textual recipes is effective for documenting food culture. However, comparing the quality of various recipes is difficult because recipe quality might depend on a variety of description styles and dishes. Therefore, we constructed the following "Comparative Recipes" dataset. First, each of the 64 writers described five recipes after watching five home cooking videos. A total of 318 recipes were created. For each dish (video), there were 15.9 recipes on average, and each recipe was described by a different writer. Next, 335 recipe readers evaluated the quality (i.e., the reproducibility and completeness) of each recipe. A morphological analysis that used this dataset revealed that the amount of description per cooking step affects recipe quality. Furthermore, the effects of cooking procedures being integrated into cooking steps on recipe quality tended to be dependent on the reader's skill. The results suggest a need for description support that appropriately integrates cooking procedures into cooking steps according to the skills and preferences of the reader.