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 at-scale 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.

Quick Actions

Share

Share this page

ios_share

https://hci.top/en/papers/chi/4786/2018

AdRecommended

Learn AI Coding at CodeNow

At a Glance

Paper Snapshot

fact_check
dataset
Source
CHI
calendar_month
Year
2018
emoji_events
Award
No award tagged
group
Authors
6 authors
sell
Subtopics
Interactive Data Visualization
work
Professions
Freelancers (Design, Writing, Translation)
article
Content Status
Abstract only
hub
Related Papers
0 related papers