What ingredient to substitute?

TAISTI is a project realised by a multi-disciplinary team developing AI-based technology for recommending ingredient substitutes in recipes.

NEWS
WORK PACKAGES
OUR SOLUTION
OUR APPROACH

Project

The TAISTI project (“Development of a Technology based on Artificial Intelligence for inferring SubsTitutable recipe Ingredients”) has received funding from the Norway Grants 2014-2021 via the National Centre for Research and Development under Small Grant Scheme.

The project is realized at the Poznan University of Technology by an interdisciplinary team of researchers between July 2021 and June 2023.

TAISTI is designed to answer specific questions aimed at solving practical problems of detecting ingredients in a recipe that should be replaced concerning a special diet, dish or other constraints and recommending their valid substitutes. The project focuses on providing practical solutions, researching various designs and experimentally evaluating them with a purpose to propose a new AI-based technology providng:

  • Integrated knowledge and data resources on culinary recipes and their ingredients to fuel artificial intelligence algorithms
  • Novel data- driven (machine learning-based) methods to recommend candidate ingredient substitutes and predict their characteristics

  • Novel knowledge-driven (logic reasoning-based) methods to select and explain target ingredients and their valid substitutes

  • Proof-of-concept system for recommending ingredient substitutes to integrate and demonstrate the developed technologies

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Publications & resources

Check latest publications and resources related to TAISTI

News

Latest news about the project

Work packages

Read about project structure

Latest Publications & Resources

  1. Dawid Wisniewski, Jedrzej Potoniec, Agnieszka Lawrynowicz: SeeQuery: An Automatic Method for Recommending Translations of Ontology Competency Questions into SPARQL-OWL. CIKM 2021: 2119-2128 https://dl.acm.org/doi/10.1145/3459637.3482387
  2. Agnieszka Lawrynowicz, Anna Wróblewska, Weronika T. Adrian, Bartosz Kulczyński, Anna Gramza-Michałowska: Food recipe ingredient substitution ontology design pattern. Sensors 22(3) (2022). https://doi.org/10.3390/s22031095


Project collaborators

We are happy to collaborate with Prof. Kerstin Bach from Norwegian University of Science and Technology (NTNU), deputy head of the Data and Artificial Intelligence group and associated with the Norwegian Open AI Lab.