RecipeScape: Mining and analyzing diverse processes in cooking recipes

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In culture analytics, it is important to ask fundamental questions that address salient characteristics of collective human behavior. This paper explores how analyzing cooking recipes in aggregate and at scale identifies these characteristics in the cooking culture, and answer fundamental questions like 'what makes a chocolate chip cookie a chocolate chip cookie?'. Aspiring cooks, professional chefs and cooking hobbyists share their recipes online resulting in thousands of different procedural instructions towards a shared goal. However, existing approaches focus merely on analysis at the ingredient level, for example, extracting ingredient information from individual recipes. We introduce RecipeScape, a prototype interface which supports visually querying, browsing and comparing cooking recipes at scale. We also present the underlying computational pipeline of RecipeScape that scrapes recipes online, extracts their ingredient and instruction information, constructs a graphical representation, and computes similarity between pairs of recipes.
Publisher
ACM Special Interest Group on Computer-Human Interaction (SIGCHI)
Issue Date
2017-05-09
Language
English
Citation

2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI EA 2017, pp.1524 - 1531

DOI
10.1145/3027063.3053118
URI
http://hdl.handle.net/10203/239300
Appears in Collection
CS-Conference Papers(학술회의논문)
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