research-article

Recipe Recommendation Method by Similarity Measure with Food Image Recognition

Authors:

Shota Tamaru,

Hyuga Taki,

Rune Usuki,

Takafumi NakanishiAuthors Info & Claims

ICISDM '22: Proceedings of the 6th International Conference on Information System and Data Mining

Pages 81 - 88

https://doi.org/10.1145/3546157.3546170

Published: 22 August 2022 Publication History

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Abstract

This paper presents a recipe recommendation method by similarity measure with food image recognition. In general, it is difficult for users with little cooking experience to find out what kind of dishes they can make from the ingredients they currently have. Therefore, we propose a system that recommends recipes based on the ingredients in the user's current inventory, thereby increasing the number of dishes in the user's cooking repertoire. This system uses camera images of foodstuffs as input, recognizes the foodstuffs, and searches for recipes. In the experiment, we conducted a questionnaire survey of the recognized food ingredients and a questionnaire survey of recipe suggestions, and the results showed that more than 3/4 of the respondents answered that the recognition results and recipe contents were correct for some of the images. In this way, possible for users to search for recipes with fewer steps.

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Cited By

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Zhang JXu YZhang HLi H(2024)Fine-Grained Food Image Segmentation Method Based on MS-Mask2Former2024 International Conference on Artificial Intelligence of Things and Systems (AIoTSys)10.1109/AIoTSys63104.2024.10780517(1-8)Online publication date: 17-Oct-2024
https://doi.org/10.1109/AIoTSys63104.2024.10780517

Index Terms

Recipe Recommendation Method by Similarity Measure with Food Image Recognition
1. Information systems
  1. Information retrieval
    1. Users and interactive retrieval
      1. Task models

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ICISDM '22: Proceedings of the 6th International Conference on Information System and Data Mining

May 2022

144 pages

ISBN:9781450396257

DOI:10.1145/3546157

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 22 August 2022

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ICISDM 2022: 2022 the 6th International Conference on Information System and Data Mining

May 27 - 29, 2022

CA, Silicon Valley, USA

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Zhang JXu YZhang HLi H(2024)Fine-Grained Food Image Segmentation Method Based on MS-Mask2Former2024 International Conference on Artificial Intelligence of Things and Systems (AIoTSys)10.1109/AIoTSys63104.2024.10780517(1-8)Online publication date: 17-Oct-2024
https://doi.org/10.1109/AIoTSys63104.2024.10780517

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Food Recipe Recommendation Based on Ingredients Detection Using Deep Learning

Recipe recommendation using ingredient networks

Real-time mobile recipe recommendation system using food ingredient recognition

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