Surprising Ingredient Extraction based on Rarity and Generality

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  • IKEJIRI Kyosuke
    Graduate School of Information Systems, The University of Electro-Communications
  • SEI Yuichi
    Graduate School of Information Systems, The University of Electro-Communications
  • NAKAGAWA Hiroyuki
    Graduate School of Information Science and Technology, Osaka University
  • TAHARA Yasuyuki
    Graduate School of Information Systems, The University of Electro-Communications
  • OHSUGA Akihiko
    Graduate School of Information Systems, The University of Electro-Communications

Bibliographic Information

Other Title
  • 希少性と一般性に基づいた意外性のある食材の抽出
  • キショウセイ ト イッパンセイ ニ モトズイタ イガイセイ ノ アル ショクザイ ノ チュウシュツ

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Abstract

Many surprising recipes exist in the user- generated recipe site. The simplest way to find surprising recipe is to use a search function. However, the title of its recipe does not always contain the keyword “surprise”. Thus we cannot find surprising recipes in an easy way. In this paper, we propose a system to extract surprising ingredients as the first step of extracting surprising recipes from the recipe site. We propose RF-IIF (Recipe Frequency-Inverse Ingredient Frequency) based on TF-IDF in our system. RF-IIF calculates a surprising value of the ingredient about the meal based on the generality and the rarity of the ingredient. We extract ingredients whose RF-IIF ranks are in top 20 as surprising ingredients about the meal. Through questionnaires to evaluate the extracted ingredients, we verified the effectiveness of the proposed method which extracts surprising ingredients.

Journal

  • Computer Software

    Computer Software 31 (3), 3_70-3_78, 2014

    Japan Society for Software Science and Technology

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