50 Ways to Bake a Cookie: Mapping the Landscape of Procedural Texts
This addresses the challenge for users in navigating thousands of independent procedural texts for tasks like cooking, though it is incremental as it applies an unsupervised learning approach to a specific domain.
The authors tackled the problem of summarizing multiple procedural texts, such as recipes, into an intuitive graph representation to help users explore commonalities and differences, with user studies showing it is intuitive and coherent for tasks like adapting recipes for novices.
The web is full of guidance on a wide variety of tasks, from changing the oil in your car to baking an apple pie. However, as content is created independently, a single task could have thousands of corresponding procedural texts. This makes it difficult for users to view the bigger picture and understand the multiple ways the task could be accomplished. In this work we propose an unsupervised learning approach for summarizing multiple procedural texts into an intuitive graph representation, allowing users to easily explore commonalities and differences. We demonstrate our approach on recipes, a prominent example of procedural texts. User studies show that our representation is intuitive and coherent and that it has the potential to help users with several sensemaking tasks, including adapting recipes for a novice cook and finding creative ways to spice up a dish.