RecipeScape: An Interactive Tool for Analyzing Cooking Instructions at Scale. Chang, M., Guillain, L. V., Jung, H., Hare, V. M., Kim, J., & Agrawala, M. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems - CHI '18, pages 1–12, Montreal QC, Canada, 2018. ACM Press. ![RecipeScape: An Interactive Tool for Analyzing Cooking Instructions at Scale [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex For cooking professionals and culinary students, understanding cooking instructions is an essential yet demanding task. Common tasks include categorizing different approaches to cooking a dish and identifying usage patterns of particular ingredients or cooking methods, all of which require extensive browsing and comparison of multiple recipes. However, no existing system provides support for such in-depth and atscale analysis. We present RecipeScape, an interactive system for browsing and analyzing the hundreds of recipes of a single dish available online. We also introduce a computational pipeline that extracts cooking processes from recipe text and calculates a procedural similarity between them. To evaluate how RecipeScape supports culinary analysis at scale, we conducted a user study with cooking professionals and culinary students with 500 recipes for two different dishes. Results show that RecipeScape clusters recipes into distinct approaches, and captures notable usage patterns of ingredients and cooking actions.
@inproceedings{chang_recipescape:_2018,
address = {Montreal QC, Canada},
title = {{RecipeScape}: {An} {Interactive} {Tool} for {Analyzing} {Cooking} {Instructions} at {Scale}},
isbn = {978-1-4503-5620-6},
shorttitle = {{RecipeScape}},
url = {http://dl.acm.org/citation.cfm?doid=3173574.3174025},
doi = {10.1145/3173574.3174025},
abstract = {For cooking professionals and culinary students, understanding cooking instructions is an essential yet demanding task. Common tasks include categorizing different approaches to cooking a dish and identifying usage patterns of particular ingredients or cooking methods, all of which require extensive browsing and comparison of multiple recipes. However, no existing system provides support for such in-depth and atscale analysis. We present RecipeScape, an interactive system for browsing and analyzing the hundreds of recipes of a single dish available online. We also introduce a computational pipeline that extracts cooking processes from recipe text and calculates a procedural similarity between them. To evaluate how RecipeScape supports culinary analysis at scale, we conducted a user study with cooking professionals and culinary students with 500 recipes for two different dishes. Results show that RecipeScape clusters recipes into distinct approaches, and captures notable usage patterns of ingredients and cooking actions.},
language = {en},
urldate = {2019-12-09},
booktitle = {Proceedings of the 2018 {CHI} {Conference} on {Human} {Factors} in {Computing} {Systems} - {CHI} '18},
publisher = {ACM Press},
author = {Chang, Minsuk and Guillain, Leonore V. and Jung, Hyeungshik and Hare, Vivian M. and Kim, Juho and Agrawala, Maneesh},
year = {2018},
keywords = {user study, clustering distinct approaches, capture usage patterns, ingredients and cooking actions},
pages = {1--12},
file = {Chang et al. - 2018 - RecipeScape An Interactive Tool for Analyzing Coo.pdf:C\:\\Users\\conny\\Zotero\\storage\\WC4ZIXHE\\Chang et al. - 2018 - RecipeScape An Interactive Tool for Analyzing Coo.pdf:application/pdf}
}
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