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Finding replaceable materials in cooking recipe texts considering characteristic cooking actions

Published: 23 October 2009 Publication History

Abstract

The number of cooking recipe texts published on the Web is increasing in recent years. However, in general, cooking recipe texts have little flexibility. So, it is not always easy to retrieve cooking recipe texts that satisfy users' various demands. Therefore, it is necessary to create and offer recipes that suit the user's requirements. In this paper, we propose a method for finding replaceable materials considering characteristic cooking actions from a large amount of cooking recipe texts. The proposed method finds the replaceable materials by first extracting the cooking actions that correspond to each material than measuring the similarity of the extracted cooking actions. Through an evaluation of recipe texts created by replacing some materials that were found by the proposed method, we verified the effectiveness of the proposed method.

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Cited By

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  • (2024)An Experimental Framework for Designing Document Structure for Users’ Decision Making: An Empirical Study of RecipesSustainability and Empowerment in the Context of Digital Libraries10.1007/978-981-96-0865-2_6(69-86)Online publication date: 6-Dec-2024
  • (2023)Cook-Gen: Robust Generative Modeling of Cooking Actions from Recipes2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)10.1109/SMC53992.2023.10394432(981-986)Online publication date: 1-Oct-2023
  • (2023)Multimodal Recipe Recommendation System Using Deep Learning and Rule-Based ApproachSN Computer Science10.1007/s42979-023-01870-64:4Online publication date: 26-May-2023
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  1. Finding replaceable materials in cooking recipe texts considering characteristic cooking actions

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    cover image ACM Conferences
    CEA '09: Proceedings of the ACM multimedia 2009 workshop on Multimedia for cooking and eating activities
    October 2009
    60 pages
    ISBN:9781605587639
    DOI:10.1145/1630995
    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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    Publication History

    Published: 23 October 2009

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    Author Tags

    1. cooking recipe
    2. recipe retrieval
    3. text mining

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    MM09
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    MM09: ACM Multimedia Conference
    October 23, 2009
    Beijing, China

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    Overall Acceptance Rate 20 of 33 submissions, 61%

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    Cited By

    View all
    • (2024)An Experimental Framework for Designing Document Structure for Users’ Decision Making: An Empirical Study of RecipesSustainability and Empowerment in the Context of Digital Libraries10.1007/978-981-96-0865-2_6(69-86)Online publication date: 6-Dec-2024
    • (2023)Cook-Gen: Robust Generative Modeling of Cooking Actions from Recipes2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)10.1109/SMC53992.2023.10394432(981-986)Online publication date: 1-Oct-2023
    • (2023)Multimodal Recipe Recommendation System Using Deep Learning and Rule-Based ApproachSN Computer Science10.1007/s42979-023-01870-64:4Online publication date: 26-May-2023
    • (2022)Towards Foodservice Robotics: A Taxonomy of Actions of Foodservice Workers and a Critical Review of Supportive TechnologyIEEE Transactions on Automation Science and Engineering10.1109/TASE.2021.312907719:3(1820-1858)Online publication date: Jul-2022
    • (2021)Using Natural Language Processing and Artificial Intelligence to Explore the Nutrition and Sustainability of Recipes and FoodFrontiers in Artificial Intelligence10.3389/frai.2020.6215773Online publication date: 23-Feb-2021
    • (2021)KNOBIE: A Design Intervention for Supporting Chefs’ Sustainable Recipe Planning PracticesProceedings of the Fifteenth International Conference on Tangible, Embedded, and Embodied Interaction10.1145/3430524.3442471(1-6)Online publication date: 14-Feb-2021
    • (2021)Market2Dish: Health-aware Food RecommendationACM Transactions on Multimedia Computing, Communications, and Applications10.1145/341821117:1(1-19)Online publication date: 16-Apr-2021
    • (2021)A Word Embedding-Based Method for Unsupervised Adaptation of Cooking RecipesIEEE Access10.1109/ACCESS.2021.30585599(27389-27404)Online publication date: 2021
    • (2021)CookingQA: Answering Questions and Recommending Recipes Based on IngredientsArabian Journal for Science and Engineering10.1007/s13369-020-05236-5Online publication date: 7-Jan-2021
    • (2020)Extraction Method for a Recipe's Uniqueness based on Recipe Frequency and LexRank of ProceduresProceedings of the 22nd International Conference on Information Integration and Web-based Applications & Services10.1145/3428757.3429128(241-245)Online publication date: 30-Nov-2020
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