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Estimating the Difficulty of Cooking Recipes by Analyzing User–Recipe Relationship in the Social Network PROCEEDINGS

, , , , , Kochi University, Japan

E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, in Kona, Hawaii, United States Publisher: Association for the Advancement of Computing in Education (AACE), Chesapeake, VA

Abstract

We have developed an algorithm to estimate the challenges in learning materials and the proficiency of learners. This algorithm uses only the learner-material network without the contents of learning materials. In this paper, we have applied it to the dataset of Cookpad, a cooking recipe community site, and have attempted to estimate the difficulty of the recipes. There is a negative correlation between the estimated difficulty ranking by using the algorithm and the accurate difficulty ranking because of the experiment, as the learners in the learner-material network prepared from the Cookpad database have unexpected characteristics. However, the strength of the correlation is decent and our algorithm proves useful for recipe difficulty estimation accordingly.

Citation

Miyoshi, Y., Fujisaki, Y., Suzuki, K., Shiota, K.i. & Okamoto, R. (2015). Estimating the Difficulty of Cooking Recipes by Analyzing User–Recipe Relationship in the Social Network. In Proceedings of E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 420-425). Kona, Hawaii, United States: Association for the Advancement of Computing in Education (AACE). Retrieved September 23, 2017 from .

Keywords