Presentation 2014-09-11
Finding Method of Replaceable Ingredients using Large Mounts of Cooking Recipes
Kento NOZAWA, Yoshiki NAKAOKA, Shuhei YAMAMOTO, Tetsuji SATOH,
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Abstract(in English) Recently, large amounts of cooking recipes are posted for sharing and searching them by many consumers. Hence there exist some similar recipes which were replaced a part of ingredients. In this study, we propose a replaceable ingredient finding method for modifying recipes by using large amounts of cooking recipes. For achieving the proposed method, we extract ingredients and cooking methods from cooking steps in each recipe. The similarities among ingredients are calculated with the word2vec, which are known as a language model based on neural network. Replaceable ingredients are indicated according to the degree of similarity among ingredients. Our experimental evaluations using several hundred thousand actual recipes demonstrate the efficiency of our proposed method.
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Keyword(in English) Cooking directions / Cooking Methods / Replaceable ingredients
Paper # DE2014-30
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Committee DE
Conference Date 2014/9/3(1days)
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Registration To Data Engineering (DE)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Finding Method of Replaceable Ingredients using Large Mounts of Cooking Recipes
Sub Title (in English)
Keyword(1) Cooking directions
Keyword(2) Cooking Methods
Keyword(3) Replaceable ingredients
1st Author's Name Kento NOZAWA
1st Author's Affiliation College of Knowledge and Library Sciences, School of Informatics, University of Tsukuba()
2nd Author's Name Yoshiki NAKAOKA
2nd Author's Affiliation Graduate School of Library, Information and Media Studies, University of Tsukuba
3rd Author's Name Shuhei YAMAMOTO
3rd Author's Affiliation Graduate School of Library, Information and Media Studies, University of Tsukuba
4th Author's Name Tetsuji SATOH
4th Author's Affiliation Graduate School of Library, Information and Media Studies, University of Tsukuba
Date 2014-09-11
Paper # DE2014-30
Volume (vol) vol.114
Number (no) 204
Page pp.pp.-
#Pages 6
Date of Issue